Human resource management and organizational performance:evidence from the retail banking sector

Underpinned by the resource-based view (RBV), social exchange theory (SET), and a theory of intrinsic motivation (empowerment), I proposed and tested a multi-level model that simultaneously examines the intermediate linkages or mechanisms through which HPWS impact individual and organizational performance. First and underpinned by RBV, I examined at the unit level, collective human capital and competitive advantage as path-ways through which the use of HPWS influences – branch market performance. Second and-, underpinned by social exchange (perceived organizational support) and intrinsic motivation (psychological empowerment) theories, I examined cross and individual level mechanisms through which experienced HPWS may influence employee performance. I tested the propositions of this study with multisource data obtained from junior and senior customer contact employees, and managers of 37 branches of two banks in Ghana. Results of the Structural Equation Modeling (SEM) analysis revealed that (i) collective human capital partially mediated the relationship between management-rated HPWS and competitive advantage, while competitive advantage completely mediated the influence of human capital on branch market performance. Consequently, management-rated HPWS influenced branch market performance indirectly through collective human capital and competitive advantage. Additionally, results of hierarchical linear modeling (HLM) tests of the cross-level influences on the motivational implications of HPWS revealed that (i) management-rated HPWS influenced experienced HPWS; (ii) perceived organizational support (POS) and psychological empowerment fully mediated the influence of experienced HPWS on service-oriented organizational citizenship behaviour (OCB), and; (iii) service-oriented OCB mediated the influence of psychological empowerment and POS on service quality and task performance. I discuss the theoretical and practical implications of these findings.

Multilevel analyses in marketing research:differentiating analytical outcomes

Marketing scholars are increasingly recognizing the importance of investigating phenomena at multiple levels. However, the analyses methods that are currently dominant within marketing may not be appropriate to dealing with multilevel or nested data structures. We identify the state of contemporary multilevel marketing research, finding that typical empirical approaches within marketing research may be less effective at explicitly taking account of multilevel data structures than those in other organizational disciplines. A Monte Carlo simulation, based on results from a previously published marketing study, demonstrates that different approaches to analysis of the same data can result in very different results (both in terms of power and effect size). The implication is that marketing scholars should be cautious when analyzing multilevel or other grouped data, and we provide a discussion and introduction to the use of hierarchical linear modeling for this purpose.

A multi-level investigation of psychological contract breach and organizational identification through the lens of perceived organizational membership:testing a moderated-mediated model

Drawing on the perceived organizational membership theoretical framework and the social identity view of dissonance theory, I examined in this study the dynamics of the relationship between psychological contract breach and organizational identification. I included group-level transformational and transactional leadership as well as procedural justice in the hypothesized model as key antecedents for organizational membership processes. I further explored the mediating role of psychological contract breach in the relationship between leadership, procedural justice climate, and organizational identification and proposed separateness–connectedness self-schema as an important moderator of the above mediated relationship. Hierarchical linear modeling results from a sample of 864 employees from 162 work units in 10 Greek organizations indicated that employees' perception of psychological contract breach negatively affected their organizational identification. I also found psychological contract breach to mediate the impact of transformational and transactional leadership on organizational identification. Results further provided support for moderated mediation and showed that the indirect effects of transformational and transactional leadership on identification through psychological contract breach were stronger for employees with a low connectedness self-schema.

Developing and leveraging human capital resource to promote service quality:testing a theory of performance

Grounded in Vroom’s motivational framework of performance, we examine the interactive influence of collective human capital (ability) and aggregated service orientation (motivation) on the cross-level relationship between high-performance work systems (HPWS) and individual-level service quality. Results of hierarchical linear modeling (HLM) revealed that HPWS related to collective human capital and aggregated service orientation, which in turn related to individual-level service quality. Furthermore, both HLM and ordinary least squares regression analyses revealed a cross-level interaction effect of collective human capital and aggregated service orientation such that high levels of collective human capital and aggregated service orientation influence individual-level service quality.

Impact of high-performance work systems on individual- and branch-level performance:test of a multilevel model of intermediate linkages

We proposed and tested a multilevel model, underpinned by empowerment theory, that examines the processes linking high-performance work systems (HPWS) and performance outcomes at the individual and organizational levels of analyses. Data were obtained from 37 branches of 2 banking institutions in Ghana. Results of hierarchical regression analysis revealed that branch-level HPWS relates to empowerment climate. Additionally, results of hierarchical linear modeling that examined the hypothesized cross-level relationships revealed 3 salient findings. First, experienced HPWS and empowerment climate partially mediate the influence of branch-level HPWS on psychological empowerment. Second, psychological empowerment partially mediates the influence of empowerment climate and experienced HPWS on service performance. Third, service orientation moderates the psychological empowerment-service performance relationship such that the relationship is stronger for those high rather than low in service orientation. Last, ordinary least squares regression results revealed that branch-level HPWS influences branch-level market performance through cross-level and individual-level influences on service performance that emerges at the branch level as aggregated service performance. © 2011 American Psychological Association.

Leveraging employee creativity through high performance work systems:a multilevel perspective

Research has looked at single rather than a configuration of human resource management (HRM) practices to influence creativity so it is not yet clear how these practices synergistically facilitate creativity and organisational performance. I address this significant but unanswered question in a three-part study. In Study 1, I develop a high performance work system (HPWS) for creativity scale. I use Study 2 sample to test the validity of the new scale. In Study 3, I test a multilevel model of the intervening processes through which branch HPWS for creativity influences creativity and branch performance. Specifically, at the branch level, I draw on social context theory and hypothesise that branch HPWS for creativity relates to climate for creativity which, in turn, leads to creativity, and ultimately, to profit. Furthermore, I hypothesise environmental dynamism as a boundary condition of the creativity-profit relationship. At the individual level, I hypothesise a cross-level effect of branch HPWS for creativity on employee-perceived HPWS. I draw on self-determination theory and argue that perceived HPWS for creativity relate to need satisfaction and the psychological pathways of intrinsic motivation and creative process engagement to predict creativity. I also hypothesise climate for creativity as a cross-level moderator of the intrinsic motivation-creativity and creative process engagement-creativity relationships. Results of hierarchical linear modeling (HLM) indicate that ten out of the fifteen hypotheses were supported. The findings of this study respond to calls for HPWS to be designed around a strategic focus by developing and providing initial validity evidence of an HPWS for creativity scale. The results reveal the underlying mechanisms through which HPWS for creativity simultaneously influences individual and branch creativity leading to profit. Lastly, results indicate environmental dynamism to be an important boundary condition of the creativity-profit relationship and climate for creativity as a cross-level moderator of the creative process engagement-creativity.

The effects of servant leadership on follower performance and well-being:underlying mechanisms, boundary conditions, and the role of training

Based on a review of the servant leadership, well-being, and performance literatures, the first study develops a research model that examines how and under which conditions servant leadership is related to follower performance and well-being alike. Data was collected from 33 leaders and 86 of their followers working in six organizations. Multilevel moderated mediation analyses revealed that servant leadership was indeed related to eudaimonic well-being and lead-er-rated performance via followers’ positive psychological capital, but that the strength and di-rection of the examined relationships depended on organizational policies and practices promot-ing employee health, and in the case of follower performance on a developmental team climate, shedding light on the importance of the context in which servant leadership takes place. In addi-tion, two more research questions resulted from a review of the training literature, namely how and under which conditions servant leadership can be trained, and whether follower performance and well-being follow from servant leadership enhanced by training. We subsequently designed a servant leadership training and conducted a longitudinal field experiment to examine our sec-ond research question. Analyses were based on data from 38 leaders randomly assigned to a training or control condition, and 91 of their followers in 36 teams. Hierarchical linear modeling results showed that the training, which addressed the knowledge of, attitudes towards, and ability to apply servant leadership, positively affected leader and follower perceptions of servant leader-ship, but in the latter case only when leaders strongly identified with their team. These findings provide causal evidence as to how and when servant leadership can be effectively developed. Fi-nally, the research model of Study 1 was replicated in a third study based on 58 followers in 32 teams drawn from the same population used for Study 2, confirming that follower eudaimonic well-being and leader-rated performance follow from developing servant leadership via increases in psychological capital, and thus establishing the directionality of the examined relationships.

Explaining the effects of class size on faculty and students

This study explored the effects of class size on faculty and students. Specifically, it examined the relationship of class size and students' participation in class, faculty interactive styles, and academic environment and how these behaviors affected student achievement (percentage of students passing). The sample was composed of 629 students in 30 sections of Algebra I at a large, urban community college. A survey was administered to the students to solicit their perceptions on their participation in class, their faculty interaction style, and the academic environment in their classes. Selected classes were observed to triangulate the findings. The relationship of class size to student participation, faculty interactive styles, and academic environment was determined by using hierarchical linear modeling (HLM). A significant difference was found on the participation of students related to class size. Students in smaller classes participated more and were more engaged than students in larger classes. Regression analysis using the same variables in small and large classes showed that faculty interactive styles significantly predicted student achievement. Stepwise regression analyses of student and faculty background variables showed that (a) students' estimate of GPA was significantly related to their achievement (r = .63); (b) older students reported more participation than did younger ones, (c) students in classes taught by female, Hispanic faculty earned higher passing grades, and (d) students' participation was greater with adjunct professors. Class observations corroborated these findings. The analysis and observational data provided sufficient evidence to warrant the conclusion that small classes were not always most effective in promoting achievement. It was found that small classes may be an artifact of ineffectual teaching, actual or by reputation. While students in small classes participate and are more engaged than students in larger classes, the class-size effect is essentially due to what happens in instruction to promote learning. The interaction of the faculty with students significantly predicted students' achievement regardless of class size. Since college students select their own classes, students do not register for classes taught by faculty with poor teaching reputation, thereby leading to small classes. Further studies are suggested to determine reasons why classes differ in size.

Resources, strategies, location determinants, and host country location choice by emerging market firms

The extant literature had studied the determinants of the firms’ location decisions with help of host country characteristics and distances between home and host countries. Firm resources and its internationalization strategies had found limited attention in this literature. To address this gap, the research question in this dissertation was whether and how firms’ resources and internationalization strategies impacted the international location decisions of emerging market firms. ^ To explore the research question, data were hand-collected from Indian software firms on their location decisions taken between April 2000 and March 2009. To analyze the multi-level longitudinal dataset, hierarchical linear modeling was used. The results showed that the internationalization strategies, namely market-seeking or labor-seeking had direct impact on firms’ location decision. This direct relationship was moderated by firm resource which, in case of Indian software firms, was the appraisal at CMMI level-5. Indian software firms located in developed countries with a market-seeking strategy and in emerging markets with a labor-seeking strategy. However, software firms with resource such as CMMI level-5 appraisal, when in a labor-seeking mode, were more likely to locate in a developed country over emerging market than firms without the appraisal. Software firms with CMMI level-5 appraisal, when in market-seeking mode, were more likely to locate in a developed country over an emerging market than firms without the appraisal. ^ It was concluded that the internationalization strategies and resources of companies predicted their location choices, over and above the variables studied in the theoretical field of location determinants.^

Influence of gender and life stressors on longitudinal depression treatment outcomes among older primary care patients

Purpose: Depression in older females is a significant and growing problem. Females who experience life stressors across the life span are at higher risk for developing problems with depression than their male counterparts. The primary aim of this study was (a) to examine gender-specific differences in the correlates of depression in older primary care patients based on baseline and longitudinal analyses; and (b) to examine the longitudinal effect of biopsychosocial risk factors on depression treatment outcomes in different models of behavioral healthcare (i.e., integrated care and enhanced referral). Method: This study used a quantitative secondary data analysis with longitudinal data from the Primary Care Research in Substance Abuse and Mental Health for Elderly (PRISM-E) study. A linear mixed model approach to hierarchical linear modeling was used for analysis using baseline assessment, and follow-up from three-month and six-month. Results: For participants diagnosed with major depressive disorder female gender was associated with increased depression severity at six-month compared to males at six-month. Further, the interaction between gender and life stressors found that females who reported loss of family and friends, family issues, money issues, medical illness was related to higher depression severity compared to males whereas lack of activities was related to lower depression severity among females compared to males. Conclusion: These findings suggest that gender moderated the relationship between specific life stressors and depression severity similar to how a protective factor can impact a person's response to a problem and reduce the negative impact of a risk factor on a problem outcome. Therefore, life stressors may be a reliable predictor of depression for both females and males in either behavioral health treatment model. This study concluded that life stressors influence males basic comfort, stability, and survival whereas life stressors influence females' development, personal growth, and happiness; therefore, life stressors may be a useful component to include in gender-based screening and assessment tools for depression. ^

Resource, Strategies, Location Determinants, And Host Country Location Choice By Emerging Market Firms

The extant literature had studied the determinants of the firms’ location decisions with help of host country characteristics and distances between home and host countries. Firm resources and its internationalization strategies had found limited attention in this literature. To address this gap, the research question in this dissertation was whether and how firms’ resources and internationalization strategies impacted the international location decisions of emerging market firms. To explore the research question, data were hand-collected from Indian software firms on their location decisions taken between April 2000 and March 2009. To analyze the multi-level longitudinal dataset, hierarchical linear modeling was used. The results showed that the internationalization strategies, namely market-seeking or labor-seeking had direct impact on firms’ location decision. This direct relationship was moderated by firm resource which, in case of Indian software firms, was the appraisal at CMMI level-5. Indian software firms located in developed countries with a market-seeking strategy and in emerging markets with a labor-seeking strategy. However, software firms with resource such as CMMI level-5 appraisal, when in a labor-seeking mode, were more likely to locate in a developed country over emerging market than firms without the appraisal. Software firms with CMMI level-5 appraisal, when in market-seeking mode, were more likely to locate in a developed country over an emerging market than firms without the appraisal. It was concluded that the internationalization strategies and resources of companies predicted their location choices, over and above the variables studied in the theoretical field of location determinants.

EXAMINING THE IMPACT OF TEACHER PRACTICE ON STUDENT LEARNING IN INTERACTIVE RADIO INSTRUCTION (IRI) CLASSROOMS: LESSONS FROM NEW DELHI AND RAJASTHAN (INDIA)

This quantitative study examines the impact of teacher practices on student achievement in classrooms where the English is Fun Interactive Radio Instruction (IRI) programs were being used. A contemporary IRI design using a dual-audience approach, the English is Fun IRI programs delivered daily English language instruction to students in grades 1 and 2 in Delhi and Rajasthan through 120 30-minute programs via broadcast radio (the first audience) while modeling pedagogical techniques and behaviors for their teachers (the second audience). Few studies have examined how the dual-audience approach influences student learning. Using existing data from 32 teachers and 696 students, this study utilizes a multivariate multilevel model to examine the role of the primary expectations for teachers (e.g., setting up the IRI classroom, following instructions from the radio characters and ensuring students are participating) and the role of secondary expectations for teachers (e.g., modeling pedagogies and facilitating learning beyond the instructions) in promoting students’ learning in English listening skills, knowledge of vocabulary and use of sentences. The study finds that teacher practice on both sets of expectations mattered, but that practice in the secondary expectations mattered more. As expected, students made the smallest gains in the most difficult linguistic task (sentence use). The extent to which teachers satisfied the primary and secondary expectations was associated with gains in all three skills – confirming the relationship between students’ English proficiency and teacher practice in a dual-audience program. When it came to gains in students’ scores in sentence use, a teacher whose focus was greater on primary expectations had a negative effect on student performance in both states. In all, teacher practice clearly mattered but not in the same way for all three skills. An optimal scenario for teacher practice is presented in which gains in all three skills are maximized. These findings have important implications for the way the classroom teacher is cast in IRI programs that utilize a dual-audience approach and in the way IRI programs are contracted insofar as the role of the teacher in instruction is minimized and access is limited to instructional support from the IRI lessons alone.

Individual and group antecedents of job satisfaction: a one-lab multilevel study

This study examines the simultaneous effect of individual (selfefficacy) and group variables (cohesion and gender diversity) on satisfaction. A laboratory study was conducted involving 373 college students randomly distributed across 79 small groups, who performed a laboratory task in about five hours. Two-level Hierarchical Linear Modeling (HLM) method was used. Results show the main effect from individual selfefficacy to satisfaction (both level 1), the cross-level effect from group cohesion (level 2) to individual satisfaction (level 1), and the interaction effect between self-efficacy and gender diversity to satisfaction. These results suggest that in a work group, satisfaction has a background in individual and group variables. Group cohesion and gender diversity have important effects on satisfaction. The article concludes with practical strategies and with limitations and suggestions for future research.

Formal modeling and analysis techniques for high level Petri nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. ^ There are two issues in using HLPNs—modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. ^ For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. ^ For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. ^ The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.^

Formal Modeling and Analysis Techniques for High Level Petri Nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. There are two issues in using HLPNs - modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.