The Mediating Impact of Goal–Role Clarity on the Relationship between Feedback–Seeking Behavior and Goal Orientations with Job Satisfaction Intrinsic Cognitions and Person–Organization Fit

Abstract

This study aims to offer a design for the cognitive calibration of employees’ work behaviors. The study focuses on fostering sustainable behavioral patterns in the workplace by arguing that, to sustain the cognitive maintenance of workplace behaviors, the nexus between self-efficacy behaviors, ability beliefs, job–role clarity, and employees’ perceived alignment should be considered during human resource (HR) processes and events, such as feedback conversations and performance reviews. The tool used to collect our data was a questionnaire administered both in paper format and digitally through an online platform compliant with European data protection regulations, to 210 professionals from two IT companies in northeastern Romania (n = 116 for the first sample and n = 94 for the second sample). The series of questions included Likert scales addressing frequency, (dis)agreement, and clarity. The model was tested using SPSS v.27 and SMART-PLS v.4 software, and the study used partial least squares structural equation modeling to examine the proposed hypotheses. Findings for Study 1 indicated that role clarity partially mediated the relationship between feedback–seeking and job cognitions whilst fully mediating the effect on person–organization fit. Results from Study 2 indicated that role clarity partially mediated the relationship between goal orientations and job cognitions and fully mediated the effect on person–organization fit. Therefore, it is possible to aid employees’ in storing their employment narratives in coherent cognitive schemas while elevating their assessment of work values’ alignment and meaningfulness. On this basis, effective tools and methodologies should be made available to employees, at the individual and team level, to help them understand the cognitive processing endorsing workplace behavioral patterns, compatibility, and causality for them to sustainably transform their workplace behavior.

1. Introduction

The volatility of employment conditions, pressure created by overexposure to a shared global economy, and the displacement of human labor by technological advances have all compelled current employees to increase their career autonomy [1].

The current work modalities, constant pursuit of competitiveness and cross-domain skills, and constant changes requiring greater resilience now dominate current work discourse [2]; therefore, the emphasis has shifted from rather disparate or singular career experiences to considering these episodes as a sequence, thereby emphasizing the necessity to develop a pattern of continuity, so that the resulting meaning-making dynamic enhances the agentic power of the individual [3].

These emerging patterns pose challenges that imply enabling of the exploration of purposeful work definitions among diverse generational cohorts [4] and redesigning the workplace with an empathic approach by prototyping employee-focused solutions that influence the quality of how workplace interactions are assessed [5] and how sustainable business performance is driven [6].

The apparent need to accommodate labor participation in a sustainable manner should motivate scholars to find micro-level solutions that improve employees’ psychological fitness [7] so that they can adapt to contemporary employment landscapes and enable organizations to reach optimum workforce sustainability through a redesign of feedback and performance review practices [8]. However, research on such employee-centric frameworks remains challenging, as the main focus in human resource research is either on employee resilience [9] or well-being [10], with minimal reference towards identifying models that could blend the transformative impact of work, as designed by employers, with a compelling work experience adaptable to employees’ changing needs.

The quest for such solutions builds on the agentic view of human functioning which is at the heart of Bandura’s social cognitive theory [11], especially the social cognitive model of career self-management [12,13], and on the empathic design of employee experience [14].

The social cognitive model of career self-management hypothesized that self-efficacy and outcome expectations relate directly to actions and indirectly through goals, upholding the adaptive behavior based on outcomes—these interrelations were confirmed by several studies in the last 25 years [13]. Moreover, future research directions pointed to the relevancy of this model being used as a template for studying career adaptability and preparedness [15] for (un)expected work events, self-advocacy behaviors on the job (e.g., feedback–seeking behavior) [16] and preparatory behavior beyond the workplace (e.g., skill updating rooted in personal evaluation of competencies), with relevant outcomes such as career satisfaction and viability based on perceived fit with the workplace dimensions [17].

The empathic design of work and of the workplace relies on the intentional curation [14] of the work design through solutions that hyper-focus the co-creation dimension of work experience and meaning [18], thereby proving an authentic understanding of the workforce and the challenges they face. The empathic design approach has the potential to enable the desired resonance of employees with the workplace experience, thereby making the sustainability challenge of employers relevant in terms of future-proofing employee retention [19] and articulating the corporate purpose of the organization through employee-centered solutions that reside in their minds long after they were implemented [20] because they provided the coherence of purpose in a more palpable manner. This approach also integrates the sustainability dimension within the “new” talent management conversation by emphasizing the need to create an organizational talent architecture that allows for multiple iterations in the pursuit of employee calibration [21]. The human resource co-creation paradigm extends the talent management and human resource theory [22] by suggesting that optimal value creation for employer and employee takes place through an interconnectivity logic of collaborative use and co-design of the employment experience [23]. The challenge for the empathic design body of literature rests with this domain having captured the interest of academia and practitioners only recently, as no theoretical models for applying design thinking into the employee experience were identified, with the concept of employee experience being fairly recent as well [14].

Considering the context previously outlined and suggested future research directions, this paper aims to explore the connection between feedback–seeking behavior and goal orientation, as feedback calibration [24] components in the workplace and perceived person–organization fit and job satisfaction, as work meaningfulness frames, mediated by job role clarity, as essential components for an employee-centric framework that could enable employers to empathically design employment experience and employees to attain clarity when cognitively processing [23] workplace causality and behavioral patterns.

We believe that such a framework would contribute to the literature on human resource management and add value to the research on fostering sustainable workplace behavior in several ways. First, it draws on the career self-management model [12] and analyzes five constructs reflecting workplace behavior, assessment, and compatibility, to examine if they could function as an employee-centric framework that contributes to desirable employee calibration and sustainable job role identification.

Second, this study answers the call for future research on the utilization of the career self-management model as a blueprint for exploring calibration and readiness for career events [13] and of the empathic design and human resource co-creation paradigm as foundational frameworks for reevaluating the underpinning assumptions on human resource process design and sustainable human resource management types [25,26].

Third, given that theoretical models are needed to further advance the sustainability dimension of human resource processes and strengthen the regenerative functionality of organizational human resource practices [26], this study theorizes and provides empirical evidence on the mechanisms through which cognitive and behavioral customization in the workplace could be observed and leveraged.

In terms of relevance and utility in the organizational realm, the micro-level solution proposed in this study would benefit employees and employers from a three-fold perspective. First, job–role clarity, proposed as a mediator variable, fosters employees’ cognitive mastery and also anchors how work environment causality is perceived [27,28]. Therefore, if coherently maintained throughout organizational changes, job–role clarity would enable employees to adjust their work capacity, while becoming increasingly aware of the depth and breadth of their functioning and participation at work in a sustainable manner [3].

Second, the literature increasingly reports that feedback–seeking behavior impacts career adaptability [15] and work role performance significantly [29] and that goal orientation is related to protean career choices and internal employability. As such, if consistently used in feedback and career-crafting conversations, they could become essential organizational tools for enhancing employee self-management and autonomy practices, facilitating the understanding of workplace behavior from a values’ alignment perspective and the cultivation of work meaningfulness [14].

Third, scholars have argued that feedback–seeking behavior is linked to how employees consider their expected job roles [15,30] and that goal orientation influences employees’ contextual sensitivity and behaviors [31], thereby nuancing their employment narratives. Determining the relationship between these factors is a prerequisite for providing organizations with a model that could foster sustainable workplace behavior at a deeper level; it could also be used to prototype employee-centric solutions during organizational changes, thus facilitating an agile transformation of ways of working [8,14,19].

Premised on the idea that job–role clarity mediates the relationship between two cognitive clarity enhancers—feedback–seeking behavior and goal orientation—and employees’ perceived alignment as reflected by perceived person–organization fit and job–satisfaction intrinsic cognitions, this study aims to offer an employee-centric framework (see Figure 1) designed to optimize how employees could calibrate their workplace behavioral patterns while steering their decision-making practices based on the alignment with their internal values’ system.

The paper is organized in the following sections: Introduction, highlighting the relevance of the proposed framework and the main aim of our exploration; Theoretical Foundation and Hypotheses Development, which has been organized into two main sub-sections, the first dedicated to the theoretical foundation of the model and component definitions and the second encompassing the hypotheses on the direct and indirect effects within the model. The third section, Materials and Methods, is dedicated to the presentation of the study population and sampling, data collection procedure, measures used in the survey, and methodology. The fourth section, Results, provides details on data screening, measurement and structural models, multicollinearity and common method bias, hypothesis testing and interpretation of direct and indirect effects. The fifth section, Discussion, is divided into four sub-sections presenting general conclusions, contributions (theoretical and practical), limitations, and suggestions for future research. In the last section, Conclusion, we indicate the originality and necessity of the research.

2. Theoretical Foundation and Hypotheses Development

2.1. Theoretical Foundation and Component Definitions

The rationale for the overall model is based on the social cognitive model of career self-management [12,13] and on empathically designing the work experience through co-creation and collaborative use [23]. The career self-management model suggests that actions are directly influenced by self-efficacy and outcome expectations, and indirectly affected by the establishment of goals, thereby promoting adaptive (work) behavior based on the outcomes attained. Similarly, approaches to the empathic design of work suggest intentionally curating an employment experience that balances employees’ needs, work requirements and commercial objectives [14] in an authentic manner and with a focus on future-proofing both human and business assets [26].

Consequently, the proposed framework explores the cognitive processing endorsing workplace behaviors and how they can be calibrated, while seeking to assess the impact of such behaviors and their corresponding mindset upon perceived workplace compatibility and causality.

The pivot component of the proposed framework is goal–role clarity defined as “the extent to which a job’s outcome goals and objectives are clearly stated and defined” [32], indicating the purposefulness of a job role as well as how individuals’ perceptions of it influence its (behavioral) interpretation. It is assumed that employees decide how to socially (re)enact their job role(s) in their workplaces, storing their employment experiences in cognitive schemas or frames [27]. This bi-fold positioning reflects two of the main tenets of social cognitive theory, namely mental processing and actions and behaviors surrounding the employee during a job role experience. Employers systematically design the roles and responsibilities within a job role experience based on strategic goals; therefore, role identification at employee level manifests based on the underlying motivational and value-based structure of job roles. Consequently, goal–role clarity also represents the proximity between a structural position in a macro-level organizational design and an individual’s cognitive and behavioral microprocesses triggered by different contexts. Thus, this dual conceptualization mirrors two perspectives from the systemic approach of a sustainable career: organizational and contextual [33].

The second construct in the framework is feedback–seeking, as its underlying logic mirrors the core notion of calibration, which concerns the discrepancy between the judgment of a situation and the accuracy of that situation [24,34] where by situation we mean performance, result, or even an experience. Calibration mirrors a metacognitive process of monitoring that reveals data about the status of knowledge or cognitive strategies applied by a person, thereby enabling the employee to exert control at a metacognitive level in order to self-regulate one’s knowledge structures and strategies [35]. Feedback–seeking is defined as the conscious effort of a proactive employee to determine the accuracy and adequacy of the behavior required to achieve a desired outcome or end state [36]. Two feedback–seeking strategies determining behavioral adequacy and accuracy were defined in feedback literature: indirect monitoring of the environment and behaviors of others, such as peers or managers, and direct inquiry regarding the perception of one’s behavior [37]. Both feedback–seeking dimensions incorporate elements of impression management and self-concept, thereby anchoring employee’s work experience. However, cognitive processing manifests differently: monitoring may necessitate greater attentional effort, whereas direct inquiry emphasizes impression management [38].

Goals represent one of the strategic components that reflect the dynamic connection between corporate objectives and employees’ purposes, connection on which sustainable employment experiences are built [39]. This connection is indicative of the way the individual interprets and responds to situations, and this meaning system influences the types of goals salient to the employee, determining the mental structure of an individual belief about the malleability of ability [40], also known as goal orientation. There are three types of goal orientation: learning goal orientation, which, according to the belief that intelligence is malleable, entails seeking to develop abilities required for future mastery of tasks; performance goal orientation, which entails seeking adequacy validation of actual competence levels; and avoidance of negative judgments about one’s abilities, which is based on the belief that intelligence is a fixed trait. All three dimensions dynamically reflect employees’ behavioral patterns, particularly in achievement contexts (i.e., task or process oriented). However, only the first two dimensions were utilized in this study, as they deal with cognitive resources centered on beliefs of effort and ability as components of achievement motivation, whereas the third dimension may trigger a threat cognitive appraisal response [31].

According to sustainable human resource management literature, human resource practices in a company influence employee performance and the felt satisfaction during the employment experience associated with a job role [41]. The perception of job role characteristics gives meaning to the way employees have agency in workplace structures, thus giving recognition to how the individual emerges from the interaction with the organized work system [18,42]. Thus, promoting sustainability over the life of the organization requires purposeful actions towards the assessment of employee enthusiasm [18], felt work compatibility and values’ alignment, which is also one of the central tenets of the human resource co-creation paradigm, namely collaborative use [23].

Person–organization fit is represented by the “compatibility between people and organizations that occurs when (a) at least one entity provides what the other needs, or (b) they share similar fundamental characteristics, or (c) both” [43], and it was conceptualized from two dimensions: perceived fit based on values and needs–supply fit. The first dimension captures the organization DNA [44] and the second dimension refers to the compatibility dynamics between employees’ needs and organizational support [45]. Perceived fit, if regularly assessed, could also indicate whether the meaning of work, as a co-created construct between individuals and groups/teams when they interact [18], shifts in an unbalanced way due to contextual discrepancies or remains balanced throughout organizational changes.

The career self-management model functions based on a dynamic interplay between self-efficacy drivers and outcomes, such as career satisfaction or skills’ development. Job satisfaction cognitions encompass employees’ evaluation of their employment experience [46] from an intrinsic and extrinsic cognitive perspective, where intrinsic job cognitions refer to how employees use competencies in the job and extrinsic job cognitions refer to recognition, interpersonal relations, and opportunities to grow [47]. Including this construct in the proposed framework would enable both employer and employee to observe the cognitive crafting of skills’ evaluation and update and leverage the resulting behavioral patterns, creating the proper space in the organizational work design for iterative learning processes.

2.2. Hypotheses Development

2.2.1. Impact of Feedback–Seeking on Job Role–Goal Clarity

When the value of demonstrating feedback–seeking behavior is reinforced by organizations, this induces an organizational routine of frequent feedback exchanges, enabling employees to pursue their objectives with more clarity and creativity while priming their skill development from multiple perspectives [48]. This workplace behavioral pattern, if encouraged, could also enable employees to identify and pursue connective paths between employment attributes, thus harnessing learning agility, which is a central outcome to sustainable career choices [49]. Despite the significant progress made in recent decades regarding the feedback–seeking concept, the focus has been on what matters in the feedback process, while relatively few studies have investigated why feedback–seeking behavior alone should be encouraged [50]. Enhancing the behavioral propensity of feedback–seeking, as a behavioral norm influencing how people work in organizations, will likely be associated with cultivating job role cognitive clarity [29].

This argument is consistent with prior research that conceptualized feedback–seeking as a behavioral strategy and demonstrated its relationships with job role–goal clarity [51] and other cognitive constructs anchored in job role–goal clarity, including career adaptability [15] and contextual performance [30]. In addition, the human resource co-creation paradigm embeds recursive feedback–seeking mechanisms that could lead to the refinement of employee experiences in various job roles. Refinement practices would also indicate intentional curation of work requirements, thus strengthening the authenticity of employee involvement in co-designing calibration paths with other relevant stakeholders [25]. Hence, we suggest the following hypothesis:

H1: 

The behavioral propensity of feedback–seeking is positively related to the cultivation of job role cognitive clarity.

2.2.2. Impact of Feedback–seeking on Person–Organization Fit

Person–organization fit represents an important component for the employment experience, since good person–organization fit has been related to organizational attraction and retention and employees’ work-related attitudes and actions [52]. It also reflects the compatibility between an individual’s values, needs, and attributes and the organization’s culture and requirements [53]. Since feedback–seeking mirrors the core notion of calibration [35] through the cognitive meta-processing of balancing accuracy and adequacy of a behavior, it facilitates the premise for employees to explore and assess how organizational and social structures within the organization create value and also allow for value co-creation. As such, we suggest that actively seeking feedback allows individuals to directly gain insights into whether their values resonate with those upheld by the organization, and whether they sense support for their values in their teams. When employees sense-making dynamic based on values manifests in a balanced way, employees respond with greater identification [54], and this desire to cooperate and collaborate could trigger either a behavioral customization when in a job role or a cognitive customization when performing a task.

Feedback–seeking behavior would allow employees to gauge the extent of organizational support for their personal and professional growth [50]. From a career viability perspective, the sense of assurance regarding their future within the organization, or lack of it, would strongly influence how work dimensions grew in significance or diminished in impact. When employees have the autonomy to seek and utilize feedback, and actively do so, it is a strong indicator of how the willingness to adapt [55], of both employer and employee, is embraced and embedded in organizational dynamics, especially when considering the needs’ fit assessment for needs that are conflicting, not complementary. Therefore, we propose the following hypothesis:

H2: 

The behavioral propensity of feedback–seeking is positively related to person–organization fit.

2.2.3. Impact of Feedback–Seeking on Job Satisfaction Cognitions

Feedback–seeking behavior, if supported and encouraged by organizations, empowers employees to actively participate in their own development [56]. Job satisfaction cognitions are grounded in a situation–action–result assessment [57], which should intrinsically evolve when the resources supporting the fulfilment of job requirements are perceived clearly [58], while progressing extrinsically when the relatedness climate is perceived as behaviorally compatible [59]. Thus, the willingness of an individual to facilitate personal and professional growth, anchored in self-efficacy drivers, should exert a significant impact on evaluative judgements of job-related outcomes. We elaborate on the potential manifestations of this impact in both intrinsic and extrinsic dimensions as follows:

From an intrinsic perspective, a pursuit for alignment is manifesting between the metacognitive self-regulatory processes triggered by monitoring peers’ behaviors and the required competency use while performing a job or a task. In other words, this dynamic balancing focuses on whether individual and systemic changes can be better calibrated through competence-feedback loops [60]. From an extrinsic perspective, a work compatibility assessment is performed through which perception of personal work behavior is calibrated utilizing direct inquiries, individuals’ experiences and interactions with peers, elicitation of collective interactions with the purpose of exchanging knowledge, facilitation of opportunities to grow, and achievement of relational goals [61].

Should these practices be implemented by an organization, it would strongly convey support and recognition for proactive behaviors and improvement-centric actions and would enable a relational architecture which would foster the development of a workforce that is self-regulating and increasingly autonomous [62]. Accordingly, we advance the following hypothesis:

H3: 

The behavioral propensity of feedback–seeking is positively related to job cognitions.

2.2.4. Impact of Goal Orientation Types on Job Role–Goal Clarity

Assessing the working environment, by using goal orientation as employees’ framework for how their employment narratives are cognitively stored, enables employers to examine how occupational self-efficacy is affected [63] and is a useful mapping of job-involvement levels [64]. However, to the best of our knowledge, studies on the potential influence of the meaning system underlying goal orientation on the cognitive scaffolding of employment attributes using components of the career self-management model are sparse.

Due to their illustrated influence on information interpretation and integration in organizations [40], mastery and prove-performance-oriented norms will likely influence how employees structure their job role cognitive schemas when enacting a job role socially or contextually. Individuals with a particular type of goal orientation will encode information in particular ways, possibly leading to different types of judgments and situated attention. Consequently, goal orientation serves as a framework for filtering information, creating meaning, and directing action, thus playing a crucial role in how employees—when assuming different job roles—experience a situation, guide the interpretation of events, and generate patterns of cognition, emotions, and behaviors [65]. This argument is also consistent with other studies demonstrating the effects of goal orientation on constructs revolving around cognitively storing work-related attributes, such as constructive resistance [66].

Thus, we submit the following hypothesis:

H4: 

Goal orientation types are positively related to how job role cognitive clarity is structured and maintained.

2.2.5. Impact of Goal Orientation Types on Person–Organization Fit

Employees impact the definition of work and how it is shaped, while the manner in which the work system is structured influences how employees build their behavioral patterns and mold their cognitive resources [64]. The way an employee perceives ability, either as a malleable construction or as a fixed structure, influences the cognitive resources allocated to perform a task, indicating effort beliefs and adequate abilities, and also determining employees’ self-regulatory practices [67]. Thus, allocation of cognitive resources plays an important role in shaping task and relational configurations at work, indicating that work meaning and purposefulness are not pre-determined but co-created from within the interaction of the employee with peers and other groups and the subsequent self-reflection practices, depending on fluid or fixed ability beliefs [68].

This interaction could impact the dynamic interplay between individual and collective value systems [69] and whether this dynamic leads to an authentic alignment, or fit, or if the interplay reveals an incongruence of values between person and organization. It could also indicate if the human capital needs are met sustainably through talent management practices [21] and forecasts on future skills. Consequently, we present the following hypothesis:

H5: 

Goal orientation types are positively related to person–organization fit.

2.2.6. Impact of Goal Orientation Types on Job Satisfaction Cognitions

As previously argued, the allocation of cognitive resources plays an important role in shaping task and relational configurations at work, thereby indicating possibilities for cognitive and behavioral customization [23] filtered by employees’ appraisal of their abilities under different frames of mind, also known as mindsets [70]. Grounded in a situation–action–result assessment, job satisfaction cognitions are expected to intrinsically develop when competency and ability use are clearly connected to task fulfilment and grow extrinsically when the relational architecture of work is perceived as compatible. We elaborate on the potential manifestations of goal orientation types on the intrinsic and extrinsic dimensions of job cognitions as follows:

Learning goal orientation encapsulates the belief that human capacities can be developed over time through personal effort and effective learning strategies [67]—thus this meaning system shapes individual willingness to be more adaptive when dealing with tensions, thus future-proofing their readiness for unexpected career events [13]. Such a mindset type would exert a considerable impact on how skills enabling individuals to do their work could be adapted, changed, or enriched either through experiential learning [71] or recursive learning processes. Moreover, the way work structures are experienced would be impacted as well, in terms of relational ties leading to recognition of discretionary effort [72] and even strengthening the foundation for psychologically safe work environments.

Performance goal orientation reflects the notion that abilities are not malleable, thus engendering a hyper-focus on success or failure before task anticipation [68]. Findings in self-efficacy studies suggested that complex task performance was influenced by employees’ sense of ability [72], as those with a performance orientation tended to avoid new experiences, thus limiting the developmental perspective, and preferred tasks they were confident they could master, shifting the focus from competency expansion to competency validation [73].

In view of these, we suggest the following hypothesis:

H6: 

Goal orientation types are positively related to job satisfaction cognitions.

2.2.7. The Consequences of Job Role Goal Clarity for Perceived Person–Organization Fit

Determining whether job role cognitive clarity endorses perceived fit based on values paired with needs–fit is another focus of this study because role identification, if coherently maintained, allows for a cognitive mapping [74] of work experiences from which employers, if they were to harness these knowledge structures, could gather valuable insights for sculpting and renewing work participation in a sustainable manner [19]. A strong association between job role cognitive clarity and perceived person–organization values and needs fit, as work meaningfulness assessment frames, is presumed for two reasons.

First, when employees perceive a comprehensive understanding of their job role’s fit and function in their workplaces, they endorse specific courses of action that demonstrate the organization’s inherent values [75]. Consequently, employers use values to cultivate an organizational culture that advocates guidelines for acceptable employee beliefs and behaviors, and employees will use these values to make decisions [76] while occupying one or more job roles.

Second, one of the central tenets of role identification is that more of employees’ needs are met when they identify more strongly with their role [28]. Accordingly, the cognitive processing underlying role identification is likely to influence the employees’ understandings of the perceived degree of congruence between the rewards from their jobs and their needs [77]. Hence, we posit the following hypothesis:

H7: 

Cultivation of job role cognitive clarity is positively related to the dynamic assessment of person–organization fit.

2.2.8. The Consequences of Job Role Goal Clarity for Job Satisfaction Cognitions

Job role clarity is believed to act as pivot component for the “I–We” merger [78] manifesting in the workplace due to the cognitive storage of employment attributes in cognitive schemas [27]. Job cognitions, as a job significance evaluation framework, stem from these employment narratives, depicting situational interpretations of these attributes through performed tasks, behavioral patterns, and interactions. The connector element between these two constructs, namely the cognitive schemas, becomes employment narratives due to information and meaning being attached to roles [79]. As such, positive associations between job role cognitive clarity and job satisfaction cognition are presumed for the following reasons.

First, when organizational roles are (cognitively) clear, then a more mindful and balanced situation–action–result assessment becomes possible, grounding an iterative learning and assessment process [80]. Second, the potential connection between these two elements would enable a furthering of our understanding of responsiveness towards skills updating from a business dynamics and individual decision-making perspective [42]. Third, these cognitive frames would allow the employer and employee to observe and document work interpretations and develop a choice architecture with opportunities to grow [81]. Accordingly, we advance the following hypothesis:

H8: 

Cultivation of job role cognitive clarity is positively related to enrichment of job-satisfaction cognitions.

2.2.9. The Mediating Role of Job Role Goal Clarity in the Relationship between Feedback–Seeking Behavior and Person–Organization Fit and Job Satisfaction Cognitions

Previously, we argued that feedback–seeking behavior, conceptualized as an employee self-efficacy construct reflecting a behavioral norm, influences work meaningfulness, as illustrated by person–organization fit and job cognitions. Leveraging these perspectives, we suggest that employee calibration could be sourced in self-efficacy and self-management. In the suggested mediation model, feedback–seeking behavior contributes to the development of job role–goal clarity [25,29]. This clarity, in turn, impacts person–organization fit [28,75,76] and job satisfaction [79].

In other words, the proposed mediation model contends that reinforced self-efficacy-driven behavioral strategies, guiding the interpretation of events from which employees can draw on many patterns of experience, should influence their cognitive clarity when storing job role employment attributes in cognitive schemas [27]. Consistent clarity when processing employment narratives, reflected in the cognitive blueprinting mechanism of role identification, should enable a consistent cognitive mapping of work experiences [74], a coherent documentation of work interpretations [81] and a comprehensive assessment of work participation and interpretation [75,77]. Therefore, employees’ individual calibration in their workplaces should be attainable. As such, we propose the following hypotheses:

H9a: 

Job role goal clarity mediates the relationship between feedback–seeking behavior and job satisfaction cognitions.

H9b: 

Job role goal clarity mediates the relationship between feedback–seeking behavior and person–organization fit.

2.2.10. The Mediating Role of Job Role Goal Clarity in the Relationship between Goal Orientation Types and Person–Organization Fit and Job Satisfaction Cognitions

In previous hypotheses, we suggested that goal orientation types, conceptualized as frameworks for how employment narratives are stored, work events are interpreted, and patterns of cognition, emotions, and behavior are generated [65,82], influence the cognitive schemas of role identification, the dynamic interplay between individual and collective values’ systems [69], competency use and experience of work structures [71,72]. Accordingly, we implicitly depicted a model in which job role cognitive clarity mediates the relationship between goal orientation types and two essential drivers, for a deeper and more profound assessment of work significance and utility.

Leveraging these perspectives, we suggest a mediation model channeling employee calibration rooted in skill flexibility perceptions and beliefs. What the model asserts is that cognitive resources allocated to a task or to a job role are conditioned by the ability beliefs of the employee [70], and this allocation influences the attachment of information and meaning to job role cognitive schemas [67], thus nuancing the resulting employment narratives. Depending on the type of goal orientation filtering these employment narratives, the role identification should indicate valuable insights regarding the dynamic interplay between individual and collective system of values [75,76], opportunities to grow through more effective decision-making practices [81] and if needs’ fulfillment channels validation or growth [73]. For these reasons, employee calibration should be achieved. Hence, we suggest the following hypothesis:

H10a: 

Job role goal clarity mediates the relationship between goal orientation types and job satisfaction cognitions.

H10b: 

Job role goal clarity mediates the relationship between goal orientation types and person–organization fit.

3. Materials and Methods

3.1. Population and Sampling

The study selected two significant IT sectors as the study population, namely outsourcing service desk solutions and automated technologies for finance and procurement processes.

Study 1 was performed in a British-owned IT company employing 250 professionals in its Bacau branch with the following job titles: IT service desk analyst, IT support specialist, resource coordinator, response center manager, and customer success manager. The job roles represented entry, medium, and senior positions within the organization chart and required skills such as advanced customer-facing and communication skills in English and in French and intermediate IT skills.

For Study 1, the sample frame comprised primarily 150 professionals who met the following criteria: a tenure of at minimum 1 year within the company (providing a basis for job role clarity) and attendance at a minimum of 8 performance management monthly cycles as feedback seeker and feedback receiver. Thus, 116 responses were collected, representing a 77.33% response rate, and were further processed for data analysis. In terms of gender, 57.8% were female, while 42.2% were male. In terms of age, most were young (42.2% under 40 years old and 40.5% under 30 years old), and in terms of tenure, 50.9% had been with their current employer for more than two years.

Study 2 was performed in a Finish-owned IT company employing 200 professionals in the Iasi branch with the following job titles: accounts payable specialist, solution consultant, customer support consultant, and support delivery manager. The job roles represented medium and senior positions in the organization chart and required skills such as customer facing assistance, basic accounting and invoicing, strong customer communication skills in English and in German, knowledge of basic cloud computing and problem-solving and analytical thinking.

For Study 2, the sample frame comprised primarily 120 professionals who met the following criteria: a tenure of at minimum 1 year within the company, thus providing a basis for job role clarity, and attendance of at minimum 2 quarterly performance management conversations with their manager, organized every quarter, and one 360-degree feedback exercise, as feedback seeker and feedback receiver with their team members. Thus, 94 responses were collected, representing a 78.33% response rate, and were further processed for data analysis. In terms of gender, 58.51% were female, while 41.9% were male. Most were young (58.5% under 40 years old), and 47.9% had been with their current employer for more than two years.

The sampling technique employed was homogeneous sampling, as we focused on candidates who shared similar characteristics, namely tenure of at minimum 1 year, exposure to feedback mechanisms, and having experienced a performance management cycle at least two times [83]. In order to ensure the legitimacy of the sample size, we used the minimum sample size requirements established by Hair et.al [84] to detect R² values of at least 0.25 (with a 5% probability of error). Given that both measurement and structural models contain a maximum of five independent variables, the required minimum of 45 observations for 80% statistical power was met for both studies.

3.2. Data Collection

Two field studies were conducted at two IT companies in northeastern Romania from January to April 2020 in a face-to-face context, pre-COVID, and from April to May 2022 in a remote context, post-COVID. We collected the data using the survey data collection method.

The first field study surveyed 150 Romanian professionals employed by a British IT company offering outsourcing service-desk solutions in Bacau County branch of northeastern Romania. The data were collected from January to April 2020 in a face-to-face context. We conducted the face-to-face survey, with the help of the Department of Learning and Development. Before disseminating the survey within the company, we presented the research objectives, research procedures, confidentiality, benefits, and consent to the Learning and Development Manager, to the Human Resources Manager, and to the managers of the operational teams targeted by the study. As benefits, for the first 50 respondents a 30 min coaching session on feedback calibration, cognitive clarity, and emotional intelligence was offered for free by one of the researchers. The collection of responses lasted four months because, during March 2020, the financial year was ending, according to the British fiscal legislation, thereby creating an overflow of tasks for the respondents. During April 2020, we communicated soft reminders in person to the managers and the team members, accommodating various preferences for the locations where respondents felt more comfortable to fill in the questionnaire. Respondents were assured all throughout the four months of data collection that there were no right or wrong answers, and that their answers would not be made public unless properly coded to avoid revealing sensitive details. In this manner, we attempted to reduce people’s evaluation apprehension.

The second field study surveyed 120 Romanian professionals employed by a Finnish IT company offering automated technologies for finance and procurement processes. The branch was based in Iasi County, northeastern Romania, and the data collection was performed from April to May 2022 in a remote working context. The survey was conducted exclusively online with the help of the Human Resources Department. Before disseminating the survey via e-mail, we presented the research objectives, research procedures, confidentiality, and consent to the country manager and to the human resources team, and we also presented the same details during an all-hands call in the beginning of May 2022, where all 200 employees attended.

Before filling out the questionnaires, participants in both studies consented to the survey in writing and participated voluntarily, without receiving any monetary compensation. All procedures were conducted in accordance with the European Union General Data Protection Regulation (GDPR) and the ethical standards of the authors’ institution.

Given that our study presented a cross-sectional design, common method bias represented a high concern; therefore, we used the following procedures to attempt controlling for its effects in terms of design of study procedure and statistical controls [85].

As to the design of the questionnaire (see Appendix A), it included three additional predictor variables, since we wanted to investigate the feedback calibration phenomena from various perspectives. Regarding the response formats, we used Likert scales addressing frequency, (dis)agreement, and clarity, separating the predictor and the criterion variables within the questionnaire by an ipsative format designed to measure four general values active in the workplace—thus, also allowing to counterbalance the question order. Furthermore, we provided two versions of the questionnaire, namely computer-based and paper and pencil, and we also used several locations for the filling of the questionnaire.

3.3. Measures

Either reflective or formative indicators must be chosen to examine a latent construct. Models with reflective measurements stipulate that all indicators should originate from the same domain, be interchangeable, and be highly correlated. Formative measurements presume that causal indicators constitute the construct, are non-interchangeable, and determine the construct’s meaning [86].

Using the five guidelines by Hair et al. [84] for distinguishing between reflective and formative constructs (e.g., causality direction, trait vs. combination, outcomes vs. causes, interchangeability, and covariation), our survey included both reflective and formative variables as well as higher-order reflective–formative constructs. Hierarchical component models (HCM) involve testing higher-order structures with two layers of constructs or dimensions [87]. Given their complexity, feedback–seeking behavior, goal orientation, and person–organization fit were modeled as higher–order reflective–formative constructs.

In order to analyze the model’s constructs, we adopted already validated measurements from the literature and followed guidelines for defining the suitable modelling. If not otherwise specified, all the measures described below used a five-point response format (1 = strongly disagree/very infrequently, 5 = strongly agree/very frequently). Please see Appendix A for the questionnaire items. For each construct, we provided the values for Cronbach’s alpha to indicate reliability of scales. All values were above the minimum threshold of 0.6 [88].

3.3.1. Feedback–Seeking Behavior (FSB)

Feedback–seeking behavior was measured using the 6-item scale developed by Ashford [89] with four reflective items used to assess monitoring behavior and two reflective items used to assess direct-inquiry behavior. Owing to the non-interchangeability of these dimensions, feedback–seeking behavior was modelled as a reflective–formative higher-order construct [86], with feedback–seeking monitoring behavior (FSBMon) and feedback–seeking direct inquiry behavior (FSBDi) as lower-order constructs. An example item is “In order to find out how well you are performing, how frequently do you compare yourself with peers?” For monitoring items, the values for Cronbach’s alpha were, in Study 1, α = 0.679, and in Study 2, α = 0.74. For direct inquiry items, in Study 1, α = 0.811 and in Study 2, α = 0.751.

3.3.2. Goal Orientation Types (GOr)

From the 13-item scale created by Vandewalle [90], 9 questions were used to measure goal orientation types, with five reflective items measuring learning goal orientation (GOrLearn) and 4 reflective items to assess prove-performance goal orientation (GOrPerf), respectively. An example item is, “I am willing to select a challenging work assignment that I can learn a lot from”. It was modelled as a reflective–formative higher-order construct because both dimensions are not interchangeable [86] and because goal orientation is a combination of both dimensions. For the assessment of goal orientation items, the values for Cronbach’s alpha were, in Study 1, α = 0.705 and, in Study 2, α = 0.883 and for performance goal orientation items, in Study 1, α = 0.817 and, in Study 2, α = 0.638.

3.3.3. Job Role Goal Clarity (GRC)

Job role goal clarity was measured using five reflective items from the 10-item scale developed by Sawyer [32]. An example item is, “Please indicate how certain/clear you are about the following aspects of your work: what aspects of my work will lead to positive evaluations”. The values for Cronbach’s alpha were, in Study 1, α = 0.899 and, in Study 2, α = 0.857

3.3.4. Person–Organization Fit (POF)

Person–organization fit was measured using the 9-item scale developed by Cable and DeRue [77] in which 6 reflective items were used to measure values’ fit (POFVal) and 3 reflective items were used to assess needs–supply fit (POFNeed), respectively. An example item is “The things that I value in life are very similar to the things that my organization values”. It was modelled as a reflective–formative higher-order construct because both dimensions combined make up the construct and are not interchangeable. For values’ fit items, the values for Cronbach’s alpha were, in Study 1, α = 0.902 and, in Study 2, α = 0.94, and for needs’ fit items, in Study 1, α = 0.914 and, in Study 2, α = 0.94.

3.3.5. Job Satisfaction Cognitions (JSCogInt)

Job satisfaction intrinsic cognitions was measured using 3 formative items from the 10-item scale developed by Williams and Anderson [91]. An example item is “I have freedom to use my own judgment”.

3.4. Control Variables

Professionals with prior experience may have preconceived notions about the types of organizations they prefer to work for, whilst those with little tenure may be more susceptible to influence by well-crafted employer (brand) messages. In turn, this influences work-related attitudes, job satisfaction perceptions, and employment decisions. Consequently, we accounted for tenure and age to reduce potential effects.

3.5. Methodology

The present study used SMARTPLS 4, a statistical software, to examine the data through partial least squares equation modeling (PLS-SEM). This method allows for the inclusion of both reflective and formative measures in the same analysis used to test the hypotheses [84]. When conducting a study aimed at uncovering significant “drivers” for the cognitive maintenance of workplace behaviors, the choice of an appropriate statistical method is crucial. Partial least squares equation modeling was considered well-suited for this study, as it provides flexibility, robustness, and predictive power while accommodating the complexities often encountered in such studies [92].

Three main arguments were considered: first, partial least squares equation modeling is particularly useful when dealing with complex models that involve both formative and reflective constructs, measurement errors, and small sample sizes. It is flexible and robust, making it suitable for exploratory studies in which the theoretical framework is not yet well-established or the sample size is limited.

Second, partial least squares equation modeling is robust to violations of multivariate normality assumptions, which is often the case with survey data collected from individuals in workplace settings [92]. In practice, workplace behavior data might exhibit non-normal distributions due to the nature of the responses or sample characteristics. Partial least squares equation modeling’s ability to handle non-normal data makes it a suitable choice for analyzing such data.

Third, partial least squares equation modeling focuses on prediction rather than explanation, making it an appropriate choice when the goal is to uncover the significant drivers of workplace behavior calibration. If the study aims to understand which factors have the most influence on cognitive maintenance of behaviors, partial least squares equation modeling can provide insights into the relative importance and strength of these drivers.

As recommended, bootstrapping (5000 re-samples) was used to calculate standard errors and approximate t-statistics for hypothesis testing [84].

4. Results

4.1. Data Screening

In order to execute the case screening, missing data was checked in rows, disengaged replies, and outliers. For Study 1 (n = 116), 6 variables with less than 5% missing values were discovered and replaced with the median for ordinal scales. Study 2 (n = 94) had no missing values. Screening in both investigations revealed no evidence of disengaged answers or outliers. In order to calculate skewness and kurtosis, SPSS 27.0 was utilized. Therefore, variables outside the recommended criteria of [−2, +2] [93] were omitted from both analyses.

4.2. Measurement Model Analysis

In the conceptual model, we included reflective and formative lower-order constructs, which we then modeled into higher-order reflective-formative constructs. As such, the measurement model analysis will include a two-stage hierarchical component models (HCM) analysis in addition to the standard structural equation modelling steps.

4.2.1. Reliability and Validity Test for Reflective Items

The reflective items in the measurement model were assessed using factor loadings, Cronbach’s alpha, composite reliability and convergent validity [94]. Based on

Table 1. Measurement Model Analysis.

Latent Variable/Indicator	Study 1 (n = 116)			Study 2 (n = 94)
	Factor Loading	Average Variance Extracted (AVE)	Composite Reliability (CR)	Factor Loading	Average Variance Extracted (AVE)	Composite Reliability (CR)
Feedback-Seeking Monitoring Behavior (FSBMon) 1st order reflective		0.74	0.85		0.65	0.84
FSBMon1	0.94			0.90
FSBMon3				0.73
FSBMon4	0.78			0.77
Feedback-Seeking Direct Inquiry Behavior (FSBDi) 1st order reflective		0.84	0.914		0.8	0.89
FSBDI5	0.89			0.88
FSBDI6	0.94			0.91
Learning Goal Orientation (GOrLearn) 1st order reflective		0.62	0.83		0.68	0.91
GOrLearn1				0.83
GOrLearn2	0.66			0.75
GOrLearn3	0.82			0.88
GOrLearn4	0.87			0.86
GOrLearn5				0.79
Performance Goal Orientation (GOrPerf) 1st order reflective		0.64	0.88		0.73	0.85
GOrPerf6	0.73
GOrPerf7	0.82			0.83
GOrPerf8	0.77
GOrPerf9	0.88			0.88
Goal Role Clarity (GRC) 1st order reflective		0.77	0.93		0.7	0.9
GoalRoleC1				0.86
GoalRoleC2	0.88			0.84
GoalRoleC3	0.86			0.86
GoalRoleC4	0.91
GoalRoleC5	0.86			0.79
Values Fit (POFVal) 1st order reflective		0.72	0.93		0.78	0.96
POFVal1	0.82			0.87
POFVal2	0.84			0.87
POFVal3	0.91			0.91
POFVal4				0.90
POFVal5	0.86			0.83
POFVal6	0.80			0.91
Needs-Supply Fit (POFNeed) 1st order reflective		0.85	0.95		0.89	0.96
POFNeed7	0.93			0.95
POFNeed8	0.90			0.94
POFNeed9	0.94			0.94

Note: The analysis was performed for reflective items loadings, by using composite reliability (CR), and convergent validity (AVE). Values were rounded to two digits for ease of readability.

, the reliability of individual items, comprising the reflective first-order constructs, was deemed satisfactory for both studies, as all composite reliability (CR) values fell within the threshold interval of [0.7, 0.9] [84]. Further, both studies met the criteria for convergent validity—per Table 1, all loadings were higher than the minimally acceptable value of 0.7, and the average variance-extracted (AVE) values for the reflective items exceeded 0.5 [94]. Values in Table 1 were rounded to two digits for ease of readability but were kept with three digits in the graphical representations.

4.2.2. Discriminant Validity for Reflective Items

The following two techniques were applied to demonstrate discriminant validity: the Fornell–Larcker criterion, the cross-loadings, and the Heterotrait–Monotrait ratio (HTMT).

First, we examined the results using the Fornell–Larcker criterion, which specifies that if the squared average variance extracted (AVE) value is higher than the inter-construct correlation, then there are no discriminant validity issues [95].

Table 2. Fornnel–Larcker Criterion.

Study 1 (n = 116)
	FSBDi	FSBMon	GOrLearn	GOrPerf	GRC	POFNeed	POFVal
FSBDi	0.92
FSBMon	0.33	0.86
GOrLearn	0.33	0.19	0.79
GOrPerf	0.09	0.13	0.16	0.8
GRC	0.33	0.28	0.19	−0.04	0.88
POFNeed	0.09	0.21	0.19	0.13	0.25	0.92
POFVal	0.17	0.23	0.14	0.14	0.35	0.61	0.85
Study 2 (n = 94)
	FSBDi	FSBMon	GOrLearn	GOrPerf	GRC	POFNeed	POFVal
FSBDi	0.89
FSBMon	0.42	0.8
GOrLearn	−0.09	0.08	0.82
GOrPerf	−0.07	0.14	0.25	0.86
GRC	0.06	0.06	0.31	−0.08	0.84
POFNeed	0.1	−0.09	0.2	−0.2	0.54	0.94
POFVal	0.03	0.04	0.3	0.01	0.52	0.55	0.88

Note: FSBMon = feedback–seeking monitoring behavior; FSBDi = feedback–seeking direct inquiry behavior; GOrLearn = learning goal orientation; GOrPerf = performance goal orientation; POFVal = person–organization values fit; POFNeed = person–organization needs fit; GRC = job role goal clarity.

presents evidence in that sense for both studies, indicating the squared average variance extracted (AVE) values in the bold diagonal.

Second, we analyzed cross-loadings. According to this approach, a specific item should have higher loadings on its own parent construct in comparison to other constructs in the study. Based on the obtained results, this criterion was met for both studies.

The final evaluation of reflective items’ discriminant validity was performed using the Heterotrait–Monotrait ratio (HTMT) ratio. Values in

Table 3. Heterotrait–Monotrait Ratio (HTMT) Correlation Matrix.

	Study 1 (n = 116)
	FSBDi	FSBMon	GOrLearn	GOrPerf	GRC	POFNeed
FSBDi
FSBMon	0.43
GOrLearn	0.44	0.29
GOrPerf	0.14	0.18	0.24
GRC	0.38	0.33	0.25	0.11
POFNeed	0.13	0.23	0.24	0.14	0.28
POFVal	0.19	0.27	0.18	0.17	0.38	0.67
	Study 2 (n = 94)
	FSBDi	FSBMon	GOrLearn	GOrPerf	GRC	POFNeed
FSBDi
FSBMon	0.58
GOrLearn	0.13	0.15
GOrPerf	0.12	0.28	0.34
GRC	0.1	0.12	0.34	0.15
POFNeed	0.12	0.11	0.2	0.25	0.59
POFVal	0.07	0.06	0.31	0.06	0.57	0.58

Note: Heterotrait–Monotrait ratio (HTMT) is the ratio of the between-trait correlations to the within-trait correlations [96]. All values are below the 0.85 threshold. FSBMon = feedback-seeking monitoring behavior; FSBDi = feedback-seeking direct inquiry behavior; GOrLearn = learning goal orientation; GOrPerf = performance goal orientation; POFVal = person–organization values fit; POFNeed = person–organization needs fit; GRC = job role goal clarity.

present evidence supporting the discriminant validity of the reflective measures, as the Heterotrait–Monotrait ratio (HTMT) values of the correlations are clearly lower than the threshold value of 0.85 [96].

4.3. Structural Model Analysis

The first step in structural model analysis concerns multicollinearity. We examined the potential for collinearity before proceeding with the path analysis by using the variance inflation factor (VIF), which assesses the degree of collinearity between indicators in a formative measurement model. We performed tests for the lower-order component job satisfaction intrinsic cognitions, modeled as a formative first-order construct (see

Table 4. Multi-Collinearity test for the formative lower-order construct.

Construct/Indicator	Study 1 (n = 116)	Study 2 (n = 94)
	VIF	VIF
Job Satisfaction Intrinsic Cognitions (JSCogInt) 1st order formative
JSCogInt1	1.464
JSCogInt2	1.3	1.208
JSCogInt5	1.39	1.208

) and for feedback–seeking behavior, goal orientation and person–organization fit, modeled as reflective–formative second-order constructs (see

Table 5. Multi-Collinearity test results for higher-order formative constructs.

Construct/Indicator	Study 1 (n = 116)	Study 2 (n = 94)
	VIF	VIF
Feedback-Seeking Behavior (FSB) 2nd order formative
FSBMon 1st order reflective	1.23	1.21
FSBDi 1st order reflective	1.23	1.21
Goal Orientation Types (GOr) 2nd order formative
GOrLearn 1st order reflective	1.06	1.12
GOrPerf 1st order reflective	1.06	1.12
Person Organization Fit (POF) 2nd order formative
POFVal 1st order reflective	1.99	1.78
POFNeed 1st order reflective	1.83	1.81

Note: FSBMon = feedback–seeking monitoring behavior; FSBDi = feedback–seeking direct inquiry behavior; GOrLearn = learning goal orientation; GOrPerf = performance goal orientation; POFVal = person–organization values fit; POFNeed = person–organization needs fit.

). The results revealed minimal collinearity, as the respective variance inflation factors (VIF) ranged between 1.033 and 1.720—far below the common cut-off threshold of 5 [92] and below the common method bias threshold of 3.3 [97].

4.3.1. Path Analysis

At this stage in the analysis, we tested the path model for significance, using bootstrapping (5000 re-samples), to establish that all of the indicators linked with the lower-order constructs (LOC) were and, therefore, contributed to the total reflective–formative second-order constructs. Additionally, because the variable job satisfaction intrinsic cognitions was modeled as a lower-order formative construct, we tested the significance for outer weights, t-value, and p-value as well. Results are presented in

Table 6. Path Analysis Results.

Paths	Study 1 (n = 116)
	Mean	STDEV	t-Value	p-Value	2.50%	97.50%
FSBDi -> FSB	0.65	0.05	13.43	0.00	0.58	0.77
FSBMon -> FSB	0.58	0.04	12.95	0.00	0.51	0.7
GOrLearn -> GOr	0.5	0.11	4.59	0.00	0.28	0.73
GOrPerf -> GOr	0.76	0.09	8.28	0.00	0.60	0.95
POFNeed -> POF	0.45	0.02	19.6	0.00	0.41	0.5
POFVal -> POF	0.66	0.03	25.46	0.00	0.62	0.72
Paths	Study 2 (n = 94)
	Mean	STDEV	t-Value	p-Value	2.50%	97.50%
FSBDi -> FSB	0.48	0.05	10.07	0.00	0.40	0.60
FSBMon -> FSB	0.69	0.05	14.31	0.00	0.61	0.81
GOrLearn -> GOr	0.96	0.03	29.4	0.00	0.89	1.00
GOrPerf -> GOr	0.12	0.06	1.81	0.07	−0.01	0.23
POFNeed -> POF	0.35	0.02	15.42	0.00	0.30	0.39
POFVal -> POF	0.76	0.04	17.77	0.00	0.70	0.88

Note: FSB = feedback-seeking behavior; FSBMon = feedback–seeking monitoring behavior; FSBDi = feedback–seeking direct inquiry behavior; Gor = goal orientations; GOrLearn = learning goal orientation; GOrPerf = performance goal orientation; POF = person–organization fit; POFVal = person–organization values fit; POFNeed = person–organization needs fit.

. All weights were typically higher than the minimally acceptable value of 0.5 [98]. Though the weight for the lower-order component in Study 2 performance goal orientation (GOrPerf) was low (0.2), the construct was retained because the t-value was above the desired 1.96 and both outer loadings for the indicators were above 0.5 and significant (p < 0.001).

4.3.2. Two-Stage Hierarchical Component Models (HCM) Analysis

To proceed with hypothesis testing, a two-stage hierarchical component models analysis was performed. In stage one, all second-order constructs were modeled using the repeated indicators approach. Accordingly, all indicators were assigned constructs, from the first order to the second order, to obtain the latent variable scores, thus addressing the issue whereby almost all of the higher-order constructs’ variance is explained by their lower order constructs, yielding an R² values of (close to) 1.0, as can be observed in Figure 2 and Figure 3 [98]; this issue arises when modeling reflective–formative hierarchical component models. In the second stage, the lower-order constructs’ scores were used as manifest latent variables in the hierarchical component model, for both studies.

4.3.3. Hypothesis Testing

Having established the validity and reliability of the outer models and having examined multi-collinearity issues, the proposed relationships within the inner model were analyzed.

Table 7. Summarized Results for Hypothesis Testing.

Hypotheses	Study 1 (n = 116)
	Paths	β	t-Value	p-Value	2.50%	97.50%	Decision
H1	FSB -> GRC	0.37	4.53	0.00	0.21	0.53	Supported
H2	FSB -> POF	0.08	0.71	0.48	−0.15	0.26	Not Supported
H3	FSB -> JSCogInt	0.23	2.41	0.02	0.03	0.41	Supported
H4	GOr -> GRC	−0.04	0.36	0.72	−0.21	0.18	Not Supported
H5	GOr -> POF	0.15	1.18	0.24	−0.11	0.38	Not Supported
H6	GOr -> JSCogInt	0.4	5.99	0.00	0.27	0.53	Supported
H7	GRC -> JSCogInt	0.25	2.52	0.01	0.07	0.45	Supported
H8	GRC -> POF	0.31	3.16	0.00	0.12	0.49	Supported
Hypotheses	Study 2 (n = 94)
	Paths	β	t-Value	p-Value	2.50%	97.50%	Decision
H1	FSB -> GRC	0.06	0.63	0.53	−0.11	0.26	Not Supported
H2	FSB -> POF	−0.02	0.22	0.83	−0.15	0.13	Not Supported
H3	FSB -> JSCogInt	−0.14	1.66	0.10	−0.3	0.03	Not Supported
H4	GOr -> GRC	0.28	2.47	0.01	0.05	0.48	Supported
H5	GOr -> POF	0.12	1.06	0.29	−0.09	0.33	Not Supported
H6	GOr -> JSCogInt	0.26	2.81	0.01	0.09	0.44	Supported
H7	GRC -> JSCogInt	0.44	3.78	0.00	0.19	0.65	Supported
H8	GRC -> POF	0.54	5.21	0.00	0.32	0.72	Supported

Note: FSB = feedback–seeking behavior; GRC = job role goal clarity; GOr = goal orientations; POF = person–organization fit; JSCogInt = job satisfaction intrinsic cognitions.

displays results of hypothesized direct effects.

Table 7 shows that H1, which assumed a positive relationship between feedback–seeking behavior and job role goal clarity, was supported in Study 1 (0.37, p < 0.001) but not in Study 2, whereas H2, which assumed a positive relationship between feedback–seeking behavior and person–organization fit was not supported in both studies. H3, which posited a direct effect between feedback–seeking behavior and job satisfaction intrinsic cognitions was supported in Study 1 (0.23, p = 0.02) but not in Study 2. The impact of goal orientation types on job role goal clarity (H4) was supported in Study 2 (0.28, p = 0.01) but not in Study 1, whereas the hypothesized relationship between goal orientation types and person–organization fit (H5) was unsupported in both studies. However, for H6, H7, and H8 supporting evidence was identified in both studies, goal orientation types being positively related to job satisfaction intrinsic cognitions (study 1: 0.4, p < 0.001 and study 2: 0.26, p = 0.01) and job role goal clarity exerting direct influence on both job satisfaction intrinsic cognitions and person–organization fit.

4.3.4. Mediation Analysis

The possibility of job role goal clarity mediating the relationships between feedback–seeking behavior and goal orientation types upon person–organization fit and job satisfaction intrinsic cognitions was examined using Hair’s [98] guidelines.

Table 8. Mediation Analysis.

Hypotheses	Study 1 (n = 116)
	Paths	β	t-Value	p-Value	2.50%	97.50%	Decision
H9A	FSB -> GRC -> JSCogInt	0.1	1.96	0.05	0.02	0.21	Supported
H9B	FSB -> GRC -> POF	0.12	2.34	0.02	0.04	0.23	Supported
H10A	GOr -> GRC -> JSCogInt	−0.01	0.35	0.73	−0.07	0.04	Not supported
H10B	GOr -> GRC -> POF	−0.01	0.35	0.73	−0.07	0.05	Not supported
Hypotheses	Study 2 (n = 94)
	Paths	β	t-Value	p-Value	2.50%	97.50%	Decision
H9A	FSB -> GRC -> JSCogInt	0.03	0.64	0.52	−0.05	0.13	Not supported
H9B	FSB -> GRC -> POF	0.03	0.65	0.52	−0.06	0.15	Not supported
H10A	GOr -> GRC -> JSCogInt	0.12	2.5	0.01	0.04	0.25	Supported
H10B	GOr -> GRC -> POF	0.14	2.76	0.01	0.05	0.27	Supported

Note: The indirect effects were calculated based on a bootstrap test with 5000 re-samples, as recommended [98]. The bias corrected and accelerated 95% confidence interval (BCaCI) with lower level = 2.5% and upper level = 97.5% should not contain a value of zero for the effect to be significant. FSB = feedback–seeking behavior; GRC = job role goal clarity; GOr = goal orientation types; POF = person–organization fit; JSCogInt = job satisfaction intrinsic cognitions.

showcases the values for the specific indirect effects obtained for both studies.

For study 1, the empirical t-value of the indirect effect (0.1) for the feedback–seeking behavior—job satisfaction intrinsic cognitions relationship was 1.96, yielding a p-value of 0.05. Similarly, for the indirect effect (0.12) of the feedback–seeking behavior—person–organization fit relationship, we obtained a t-value of 2.34, indicating a p-value of 0.02. The next step focused on the significance of the direct effects of feedback-seeking behavior on job satisfaction intrinsic cognitions and of feedback–seeking behavior on person–organization fit. The feedback–seeking behavior—job satisfaction intrinsic cognitions relationship was moderate (0.23) and statistically significant (t = 2.41 and p = 0.02), while the effect of feedback–seeking behavior on person–organization fit was weak (0.08) and nonsignificant (t = 0.71 and p = 0.48). Therefore, we concluded that GRC partially mediated the relationship between feedback–seeking behavior and job satisfaction intrinsic cognitions, since both the direct and indirect effects were significant. In order to substantiate the type of partial mediation further, we computed the product of the direct and indirect effects, which was positive. Accordingly, job role goal clarity mediated the relationship between feedback–seeking behavior and job satisfaction intrinsic cognitions complementarily. We concluded that job role goal clarity fully mediated the feedback–seeking behavior—person–organization fit relationship, since the direct effect was non-significant, but the indirect effect was significant. Consequently, Study 1 supports H_9a and H_9b but not H_10a and H_10b.

For Study 2, the empirical t-value of the indirect effect (0.12) for the goal orientation types–job satisfaction intrinsic cognitions relationship was 2.5, yielding a p-value of 0.01. Similarly, for the indirect effect (0.15) of the goal orientation types–person–organization fit relationship, we obtained a t-value of 2.76, indicating a p-value of 0.01. The next step focused on the significance of the direct effects of goal orientation types on job satisfaction intrinsic cognitions and goal orientation types on person–organization fit. The goal orientation types—job satisfaction intrinsic cognitions relationship was moderate (0.26) and statistically significant (t = 2.81 and p = 0.01), while the effect of goal orientation types on person–organization fit was weak (0.12) and non-significant (t = 1.06 and p = 0.29). Therefore, we concluded that job role goal clarity partially mediated the goal orientation types—job satisfaction intrinsic cognitions relationship, since both the direct and the indirect effects were significant. In order to substantiate the type of partial mediation further, we computed the product of the direct and the indirect effects, which was positive. Accordingly, job role goal clarity mediated the goal orientation types—job satisfaction intrinsic cognitions and goal orientation types—person–organization fit relationships complementarily. We concluded that job role goal clarity fully mediated the goal orientation types—person–organization fit relationship, since the direct effect was non-significant, but the indirect effect was significant. Consequently, Study 2 supports H_10a and H_10b but not H_9a and H_9b.

5. Discussion

5.1. General Conclusions

The present study aimed to investigate the relationships between job role clarity, feedback–seeking behavior, goal orientation types, and various work meaningfulness’ assessment frames, so as to identify potential cognitive calibration paths for employees’ work behaviors. Out of 8 hypotheses formulated regarding potential direct effects between examined constructs, 4 yielded nuanced conclusions and 4 produced similar results for the work environments in which both studies were performed, namely face-to-face for Study 1 and exclusively remote for Study 2. The results obtained for the 4-mediation hypothesis indicated divergent findings, thereby highlighting the importance of considering the work environment when exploring the suggested relationships and the possibilities for the calibration of workplace behavioral paths. We continue with a summary of the results obtained for every hypothesis.

The results for Hypothesis H1, examining the impact of feedback–seeking on job role cognitive clarity, yielded nuanced conclusions. Study 1 provided strong evidence supporting the hypothesis, aligning with previous research emphasizing the benefits of feedback exchanges in fostering skill development, learning agility, and personal control [48,49]. However, Study 2 presented counterevidence, aligning with research results confirming that remote working dynamics affects the feedback–seeking behavior of employees and the effect of feedback–seeking on role clarity [99,100]. These contrasting outcomes highlight the importance for employers to ensure a foundation for meaningful feedback–seeking practices customized to actual work and relational architecture.

The results for Hypothesis H2, examining the impact of feedback–seeking on person–organization fit, presented counterevidence in both studies, suggesting that feedback– seeking may not be a decisive factor in determining the compatibility between an individual’s values, needs, and attributes with the organization’s culture and requirements [53]. The shift to remote work in Study 2 may have influenced employees’ perceptions of organizational values, potentially affecting their sense of fit [52]. The lack of a significant direct association in both work settings prompts further investigation into potential mediating factors, such as work design or role clarity, which we hypothesized in H9a, H9b, H10a and H10b.

Hypothesis H3 yielded intriguing and contrasting conclusions regarding the complex relationship between feedback–seeking behavior and job cognitions. Study 1 provided compelling supportive evidence, indicating that feedback–seeking behavior is positively related to job cognitions, empowering employees to actively participate in their own development [56,57]. The cultivation of metacognitive self-regulatory processes and work compatibility assessment facilitated a dynamic balancing of individual and systemic changes, promoting proactive behaviors and improvement-centric actions [62]. However, Study 2 presented counterevidence, suggesting no significant positive relationship between feedback-seeking behavior and job cognitions [59]. The limited opportunities for direct inquiries and knowledge exchange might have hindered employees’ perceptions of their development and work-related outcomes, as suggested in other studies on remote work challenges and the new cognitive demands it poses [101].

Hypothesis H4 underscored the complexity of the relationship between goal orientation types and job role cognitive clarity, with contrasting results in face-to-face and remote work environments. In a remote work setting, goal orientation types appeared to have a more pronounced impact on employees’ cognitive schemas and judgments regarding job roles compared to a face-to-face work environment, where the findings indicated further exploration into the potential factors influencing the cognitive scaffolding of employment attributes and job-involvement levels.

Hypothesis H5 posited a positive relationship between goal orientation types and person–organization fit, indicating that employees’ perceptions of ability and cognitive resource allocation would directly influence the alignment of individual and collective values within the organization. The counterevidence from both studies challenges this hypothesis, suggesting that goal orientation alone may not be sufficient to predict person–organization fit as it may interact with other contextual factors and self-regulatory practices [67]. Furthermore, the interplay between individual and collective values and the alignment of human capital needs within the organization might be more intricate than the impact of goal orientation types alone [68].

The findings from Study 1 and Study 2 offer strong supporting evidence for Hypothesis H6, indicating a positive relationship between goal orientation types and job satisfaction cognitions. The dynamic nature of this relationship offers valuable insights into employee calibration mechanisms, as it aligns with research on priming mindset dynamics and its impact on sustainable careers [48] and also supports mindsets’ mapping and embedding in workplace contexts [102].

Hypothesis H7 proposed a positive relationship between job role cognitive clarity and the dynamic assessment of person–organization fit, indicating that employees’ clear understanding of their job roles would endorse perceived fit based on values paired with needs fit—supporting evidence was obtained from both studies. The findings suggest that a cognitive mapping of work experiences would be possible [74], capturing insights on value alignment and needs’ fulfillment.

The substantiating data for both studies pertaining to Hypothesis H8 emphasizes the intricate relationship between job role cognitive clarity and job satisfaction cognitions, indicating that cognitive clear frames of role identification supported mindful situation–action–result assessments, thereby enhancing accuracy of work interpretations and decision making. These insights align with research on work transformation and participation solutions allowing for a balanced design of agency in hybrid workplace platforms [103].

Hypotheses H9a and H9b proposed that job role goal clarity mediates the relationship between feedback–seeking behavior and job-satisfaction cognitions (H9a) and between feedback–seeking behavior and person–organization fit (H9b). The contrasting findings between Study 1 and Study 2 highlight the relevancy of adapting feedback–seeking mechanisms in different work environments to optimize role identification and the cognitive storage of employment attributes. The challenges of remote interactions may have impacted how employment narratives were processed, affecting employees’ sense of coherence, personal control, and agency.

Hypotheses H10a and H10b posit that job role goal clarity acts as a mediating factor in the relationship between goal orientation types and job satisfaction cognitions (H10a) and between goal orientation types and person–organization fit (H10b). Divergent results between Study 1 and Study 2 indicate the complexity of how goal orientation types interact with cognitive schemas, affecting self-reflection practices, value alignment, and perception of needs’ fulfillment.

Based on the results for each hypothesis, supporting and nuanced, we believe that the indicated constructs could potentially function as an employee-centric framework, as the confirmed relationships within the model further the research on cognitive maintenance of work behaviors—providing organizations with a prototype for crafting and assessing employee-centric solutions and providing employees with opportunities for cognitive calibration in their workplaces, in terms of self-efficacy and meaningfulness assessment. The divergent relationships between the constructs showcase the necessity of further exploration on how cognitive and behavioral customizations manifest in a remote work context, upholding the iterative logic required to reevaluate assumptions of HR process design.

5.2. Contributions

5.2.1. Theoretical Contributions

This study contributes to the body of literature on fostering sustainable workplace behavior, cognitive calibration in the workplace, and the co-creation paradigm in several ways.

First, integrating feedback–seeking behavior, goal orientation, and goal–role clarity into a single study enabled our research to build upon and extend the application of self-management career model by examining the interconnectedness of these concepts and exploring how they interact and influence one another in various work contexts. As the explored relationships reflected potential paths of career preparedness and the synergistic effect between adaptable workplace behavior, ability beliefs, and assessment of workplace dimensions, we consider this framework appropriate for engendering sustainable workplace behavioral patterns.

Second, the pivot component of the model, goal–role clarity mediated the relationship between feedback–seeking behavior, goal orientation types, and two work meaningfulness frames in both face-to-face and virtual workplaces. The mediation effects, be they partial or total, indicated that role cognitive clarity plays a crucial role in promoting a more accurate depiction of the cognitive processing underlying perceived workplace causality and compatibility, as well as enhancing intrinsic cognitive job satisfaction and perceptions of fit within an organization, both of which are key to promoting sustainable workplace behavior. Consequently, the depicted co-created structure of role identification indicates the regenerative potential of the job role design within the organizational chart, supporting the co-creation paradigm while furthering a path for fostering the sustainability dimension of human resources process design.

Third, the research showed that feedback–seeking mechanisms presented an amplified intensity in the face-to-face workplace compared to the remote one, suggesting that employee cognitive self-adjustment, when evaluating employment narratives, may shift when workplaces structures evolve, thus emphasizing why intentionally curating work design is a relevant and much-needed action for future-proofing employee retention. Findings on goal orientation types indicated, in support of the same empathic design perspective, that the meaning system behind ability beliefs influences cognitive clarity when storing employment attributes and the implicit allocation of cognitive resources shapes willingness for adaptability and competency validation. This can inform strategies to promote sustainable workplace behavior due to the cognitive and behavioral customization possible based on previously described relations.

This research illustrates how employees’ individual calibration in their workplaces can be leveraged intrinsically, thus contributing to the literature on sustainable workplace behavior, and extrinsically, adding to the body of literature on the co-creation paradigm and empathic work design.

5.2.2. Practical Contributions

The findings of this study contribute to our understanding of the dynamics between job role clarity, feedback–seeking behavior, and goal orientation types as crucial elements influencing employees’ cognitive experiences and workplace behavioral patterns.

The notion that these constructs can be utilized for an empathic (re)design of the employment experience is particularly relevant in today’s dynamic and rapidly changing work environments. It emphasizes the importance of addressing employees’ self-efficacy and meaningfulness assessments, as these factors play a vital role in shaping their behaviors and overall job satisfaction. For instance, organizations can develop training programs and resources that facilitate feedback–seeking behaviors and promote a culture of open communication, where employees are encouraged to seek feedback and actively engage in conversations about their job roles. Such an approach could facilitate employees’ well-being, engagement, and intrinsic motivation [104].

Second, understanding employees’ goal orientation types can inform the design of performance management systems, career development programs, and motivational strategies. Organizations can tailor these initiatives to align with employees’ mastery or performance goal orientation, providing them with opportunities for growth, learning, and competence validation. By recognizing the influence of goal orientation types on job role clarity, organizations can create environments that foster employees’ cognitive calibration and enhance their self-efficacy and perceived meaningfulness in their work. The resulting cognitive balancing would result in a consistent and sustainable architecture of employment narratives, thereby producing a signature experience [105].

However, it is important to note that the implementation of these employee-centric solutions may require careful planning, resources, and ongoing evaluation, as well as iterative learning processes gradually embedded in the human resources’ processes. Organizations should continuously assess the effectiveness of their interventions and make necessary adjustments to ensure that they are meeting the cognitive needs of their employees. Furthermore, this iterative process of assessment, design, and adaptation contributes to the sustainable development of workplace behavior and fosters a culture of continuous improvement. When properly mapped, situational behaviors reveal whether the I–We merger [78] is unfolding organically or whether there are blocking points. When responses generate inconsistent narratives, managers and human resource executives could use the framework of this study to address employees’ perception of a gap between the promised and actual employment experience, thereby empathically redesigning their processes and molding them to employees’ behaviors and identified or expressed needs, rather than imposing arbitrary pathways from traditional people-management systems.

As such, this study’s results advocate incorporating these constructs into the organizational fabric so as to enable organizations to create supportive and engaging workplaces that promote employees’ cognitive calibration, self-efficacy, and perceived meaningfulness. Further research in this area could expand our knowledge and provide organizations with valuable prototypes for employee-centric solutions that foster cognitive well-being and enhance work experiences, especially because this inclusive and empathic approach has the potential to enhance workplace behavior sustainably and contribute to the long-term success and growth of both employees and organizations.

5.3. Limitations

Despite the careful planning and execution of the study, there are several limitations that we need to acknowledge. First, the design of the study was cross-sectional, which limits our ability to infer causality. Longitudinal or experimental designs in future studies could help in providing more robust evidence for the directionality of the relationships examined in this study.

Second, this study is limited to IT outsourcing staff; thus, caution is recommended when extrapolating the results to other industries or business types. This study was conducted at two outsourcing corporations in northeastern Romania prior to and after the COVID-19 outbreak; its generalizability could be improved by drawing samples from other regions of the country and IT outsourcing workers who have both onsite and remote work experience.

Third, despite measures taken to minimize common method bias, including the design of the questionnaire, separation of predictor and criterion variables within the questionnaire, using Likert scales and ipsative formats, and the provision of two versions of the questionnaire (computer-based and paper-and-pencil), there might still be some residual common method variance. This is because the data used were self-reported, which could be subject to biases such as social desirability or acquiescence bias. Future studies should consider incorporating other types of data, such as supervisor or peer evaluations, or objective measures where possible to corroborate self-report data.

Fourth, although we used a reflective–formative approach to model our constructs, alternative modeling approaches could potentially yield different results. Therefore, researchers should also consider alternative modeling approaches in future studies.

Last, our model considered several important variables based on previous literature, but other potential variables could influence the relationships we examined. Other relevant constructs such as feedback accountability, perceived organizational support, and elements of organizational culture could be incorporated into future research to provide a more comprehensive understanding of the dynamics within the sustainable fostering of workplace behavior.

5.4. Suggestions for Future Research

While our study provides important insights into the relationship between job role clarity, feedback–seeking behavior, goal orientation, and fostering sustainable workplace behaviors, there are areas for further research. Future studies could explore additional constructs or variables that may influence the cognitive experiences of employees and further refine our understanding of the empathic (re)design of employment experiences. For example, multi-source studies on feedback calibration may be conducted with additional outcome variables related to work meaningfulness and utility assessment, such as perceived organizational support or affective and intellectual engagement.

Longitudinal studies designed for employee experience and behavioral patterns’ mapping, comparing the efficacy of this model in various time-constrained projects involving similar teams could provide valuable insights into the long-term effects of cognitive clarity on employee well-being, job satisfaction, and organizational performance.

Even though our study hypothesized and tested certain directional relationships between the variables, it is also possible that these relationships could be bidirectional or even reverse to what we have hypothesized. For example, we hypothesized a positive relationship between feedback–seeking behavior and goal role clarity as well as a positive relationship between goal orientation types and goal–role clarity. While our findings provided support for these relationships in one study or another, it could be that goal–role clarity also influences feedback–seeking behavior and goal orientation types. In other words, the clarity of role goals in the organization might encourage or discourage individuals to seek feedback or adopt a particular goal orientation, and this could vary greatly depending on the specific nature and norms of the role goals. Similarly, we suggested that goal–role clarity mediates the relationships between feedback–seeking behavior or goal orientation types and job satisfaction intrinsic cognitions and perceived organizational fit. It might be possible that employees who have a higher level of intrinsic cognitive satisfaction in their jobs or perceive a better fit with their organization might perceive their role goal clarity differently, or they might engage in more feedback–seeking behavior or show a different level of goal orientation.

These potential reverse causal relationships and bidirectional influences highlight the complexity of the constructs we are studying. While beyond the scope of our current study, future research should consider exploring these potential reverse and reciprocal relationships, ideally utilizing longitudinal designs that can better capture these dynamics over time.

6. Conclusions

Our study provides significant support for the benefits of structurally embedding the cultivation of cognitive clarity within organizations, benefiting both employees and the organization as a whole. The proposed employee-related constructs serve as a micro-level solution for the empathic (re)design of employment experiences, originally illustrating the embedded accountability and relational dynamics that shape employees’ work experiences. Additionally, these constructs enable employees to engage with people management practices in a connected manner, fostering a sense of meaningfulness and facilitating the organization’s ability to shape its DNA in a sustainable manner.

By incorporating the constructs of job role clarity, feedback–seeking behavior, and goal orientation, organizations can create an environment that fosters cognitive clarity and empowers employees to navigate their roles and responsibilities effectively. Our statistical analyses demonstrated that these constructs portray in a novel manner the manifestation of employment narratives and highlight in a fresh and creative manner possibilities to observe and leverage the meaning-making dynamics within the organization.

The micro-level solution based on the influence between proposed constructs allows organizations to document and understand the interdependencies between different facets of the employment experience. By doing so, valuable insights could be gained from employees in terms of their capabilities and the organization’s competitiveness. The implementation of these constructs for an empathic (re)design of employment experiences requires a strategic and holistic approach. Organizations should consider integrating these constructs into their human resource management practices, training programs, and performance management systems. By doing so, organizations can create an environment that sustainably supports employees’ cognitive well-being, self-efficacy, and perceived meaningfulness.