The relationship between four contextual factors on resistance to change: A case study in food processing industry

Nội dung text: The relationship between four contextual factors on resistance to change: A case study in food processing industry

1. THE RELATIONSHIP BETWEEN FOUR CONTEXTUAL FACTORS ON RESISTANCE TO CHANGE: A CASE STUDY IN FOOD PROCESSING INDUSTRY MA. Tran Trong Duc1 – Nguyen Dieu Linh2 Abstract: Empirical and practitioner findings relating to change management indicated an unfavorable trend in successful change management for the last decade. The term “Lean” was used to describe an approach enabling firms to maximise customer value while minimising waste by eliminating inefficient and unnecessary processes and enhancing the value chain. The most prevalently applied lean tools include just-in-time, value stream map, total quality management, kaizen, and total productive maintenance. When considering in a specific context of Lean transformation, the change failure rate was reported to be even lower in various contexts. This paper chose to investigate a single-case study in Lean transformation, a manufacturing plant adopting one of the Lean tools – Total Productive Maintenance, in food processing industry. The purpose of this research is to uncover whether and how contextual factors (information exchange, participation, trust in management and training), related to resistance to change (RTC). Keywords: Resistance to change, Information exchange, Participation, Trust in management, Training, Perceived impact of change. 1. INTRODUCTION Empirical and practitioner findings relating to change management indicated an unfavorable trend in successful change management for the last decade. Till recent years, the statistics were not showing any improvement and stil at the rate of 70% for change effort to fail (Michel et al., 2013; Al-haddad and Kotnour, 2015). When considering in a specific context of Lean transformation, the change failure rate was reported to be even lower in various contexts. Recent studies such as Schipper and Swets (2010) and Jadhav et al. (2014) reported that 70% of lean transformation cases failed in overcoming barriers and returned to the previous ways of performing work. However, in the case of UK organizations, the success rates in Lean transformation remained to be at 10% throughout the years (Camagu, 2010; Bhasin and Burcher, 2006; Baker, 2002). Mohanty et al. (2007)’s survey findings indicated that US organizations, particularly in automobile industry, were struggling to imitate Toyota Production System to achieve operational efficiency. Extant research constantly cited resistance to change (RTC) from employees as one of the key problems for change failure (Huang and Huang, 2009; Erwin and Garman, 2010). Managing resistance is critical determining whether the change implemented will be successful or not (Decker et al., 2012; Canning and Found, 2015) since resistance has the power to slow and prevent change from happening (Coetsee, 1999). Therefore, resistance to change should be given sufficient attention by management, especially in the rapidly changing business environment when the needs to changes are raised 1 National Economics University. Email: ductt@neu.edu.vn. 2 National Economics University.Email: nguyenlinh090998@gmail.com. 765
2. constantly. This paper aims to investigate antecedents of RTC (contextual factors, to be specific), to assist management make informed decision dealing with RTC. Considering the extant gap in the literature relating to both context of Vietnam and quantitative research on Lean transformation, this study chose to investigate a single-case study in Lean transformation, a manufacturing plant adopting one of the Lean tools – Total Productive Maintenance, in food processing industry. Reviewing the literature in lean and resistance to change, four key employee factors when implementing Lean – trust in management, training, information exchange and participation (Cudney and Elrod, 2010; Jadhav et al., 2014; Canning and Found, 2015; Carroll, 2005; Portioli-Staudacher and Tantardini, 2012) – are chosen as four contextual factors to analyse its relationships with RTC. 2. LITERATURE REVIEW 2.1. Resistance to change In the conventional view on organizational change, organizational change is considered as desirable and inevitable; and people resisting it are irrational. This view implied that resistance should be managed and overcome (Mabin et al., 2001; Piderit, 2000, Atkinson, 2005). Dent and Goldberg (1999) proposed that individuals resist negative consequences (e.g., losing their jobs, disrupting daily works) and not necessarily the change in itself. Therefore, the conventional belief hinders organizations’ holistic understanding of RTC. Considering defining RTC issues, Jermier et al. (1994, p.94), Dent and Goldberg (1999) pointed out that RTC has been oversimplified, referred to any unfavourable reactions to prevent change. To better grasp the complexity of resistance, suggesting that a dichotomous perspective of employees’ response to change (pure resistance and compliance) was too narrow, Piderit (2000) defined RTC as a tri-dimensional (negative) response towards change, which includes how individual feels about change (affective), intentions to act towards change (behavioural), and what they think about change (cognitive). In this study, RTC is examined in the behavioural dimension, which involves behaviours or intentions to behave responding to the change (e.g., protesting against change, presenting disagreement to upper management levels, etc.). To examine employees’ RTC, this study chose to investigate the concept from the perspective of change recipients referring to the group of people taking charge of implementing or adapting to changes (Jacobs and Keegan, 2016), since they are the most appropriate to measure their own perceived resistance (Armenakis and Harris, 2009; Oreg et al., 2011). When reviewing extant literature on RTC, the pioneering works of Lewin (1947) and Coch and French (1948) initially proposed that potential sources of resistance come from both the individual and one’s environment – contextual factors. However, owning to reducing interest in field theory, papers followed these 2 works focused on the individual and how they reacted to change and tend to omit contextual factors (Burnes, 2014). Consequently, followed papers such as Bovey and Hede (2001), Dent and Powley (2003), Weller and Bernadine (2007), Smollan (2011) growingly refer RTC as a psychological concept in which resistance is within individual employees. For instance, due to prevalence of Oreg (2003)’s study in dispositional resistance concept, sources of RTC were increasingly viewed at personality perspective, which leads to the lack of academic attention on contextual factors. Following Burnes (2014) call on research focus on contextual factors to support for Coch and French (1948) and Lewin’s (1947) system view of resistance, the paper aims to investigate 766
3. RTC antecedents in contextual view, in the context of Vietnam – where the investigation of RTC and its contextual antecedents is still highly limited. Shani et al. (2010, p.240,241) and Oreg et al. (2011) categorized contextual factors into 4 major types: the first type (1) – internal context antecedents involving pre-change organizational environment including culture and climate, trust in management; the second type (2) change process antecedents comprising of participation; communication and information and principal support during change; the third type (3) – perceived outcomes/impact of change; and the last type (4) change content antecedents (M&A, downsizing). In the context of Vietnam, affected commitment, participation and communication were empirically investigated in Manh Hung (2017)’s paper, examining RTC in organizations conducting changes, in general. This paper fills in the knowledge gap by re-testing the impact of participation and information exchange in a specific Lean case study, and examining two narrowly investigated contextual factors – trust in management and training in Vietnam. 2.2. Resistance to change in Lean Transformation The term “lean” was first used by Womack et al. (1990) to describe an approach enabling firms to maximise customer value while minimising waste by eliminating inefficient and unnecessary processes and enhancing the value chain (Womack and Jones, 2003; Chual et al., 2010). The most prevalently applied lean tools include just-in-time, value stream map, total quality management, kaizen, and total productive maintenance (Marodin and Saurin, 2013). Though organizations widely implement lean tools to achieve its desired outcomes, the lean successful implementation rate is recognized to be significantly low – approximately 10% in various countries such as UK, India, US in extant literature (Mohanty et al., 2007; Camagu, 2010; Singh et al., 2010), due to three key barriers involving cultural, human and geographical factors (Benton and Shin, 1998). In which, employee barriers to lean implementation mostly relate to ineffective communication, inadequate information exchange between managers and employees (Cudney and Elrod, 2010; Jadhav et al., 2014); lack of participation in decision-making from employees (Canning and Found, 2015; Carroll, 2005; Portioli-Staudacher and Tantardini, 2012), lack of formal training to employees (Eswaramoorthi et al., 2011), and lack of mutual trust between employees and managers (Staudacher and Tantardini, 2007). Specifically, Sim and Chiang (2012) and Azyan et al. (2017) identified key sources for employee resistance in lean program, which involves trust in management; negative perceived impact of change (increasing workload, being undervalued because of lean). However, reviewing literature, the number of empirical studies on employee resistance in Lean case study is still limited, especially in Vietnam context. In lean literature, the majority of papers on employee resistance adopts qualitative research, interviews to be specific, such as Sim and Chiang (2012) and Azyan et al. (2017). Also, only a few contextual factors such as communication and participation were empirically tested in lean context (Canning and Found, 2015). Therefore, this study fills in the research gap by testing four key identified human barriers in Lean implementation – information exchange, participation, training, trust in management as factors affecting employee resistance in a Lean case study in Vietnam. 2.3. Conceptual framework 767
4. Figure 1: Coneptual framework 2.3.1. Information exchange Information exchange refers to the degree to which recipients perceive that the necessary and useful information relating to organizational change is provided and those provided information must be exchanged timely and delivered effectively (Miller et al., 1994; Armenakis et al., 2007; Holt et al., 2007). Previously empirical studies in extant literature have found that individuals equipped with necessary information have higher level of likelihood to adapt to change (Schweiger and DeNisi, 1991; Miller et al., 1994). Lewis’s (2006) study surveying undergraduates working part-time in organizations implementing new information technology program in various industries, also found that the better the perceived quality of received information, the lower the degree of one’s resistance to change. In the context of Vietnam, Manh Hung (2017) testing the relationship in organizations implementing changes in general, in various industries, suggested a similar finding to Lewis’s (2006). Putting in the Lean transformation context, Cudney and Elrod (2010) and Scherrer-Rathje et al. (2009) addressed the importance of appropriately informing about the change to employees to tackle resistance and raise success rate of Lean implementation. For instance, if lean expected process and outcomes were not communicated well to all functional areas; employees in frontline may not be fully aware of the program, then results in higher level of stress and increase likelihood to behave opposingly towards change due to uncertainty and ambiguity of information (Jadhav et al., 2014; Schweiger & Denisi, 1991). 2.3.2. Participation Participation is defined as employee involvement in the decision-making process in the development and implementation of the change initiative, as well as the right to input decisions of the change’s future plans (Lines, 2004; Giangreco and Peccei, 2005, Wanberg & Banas, 2000). Looking into change management literature, Cornell and Herman (1989); Fiorelli and Margolis (1993); Wanberg and Banas (2000) unanimously argued the impact of employee involvement in addressing resistance, particularly, when employees have the rights to input decisions, their 768
5. commitment to the change increased and resistance to change reduced, accordingly. Also, Lines’s (2004) study in a restructuring project in a telecommunication case study and Msweli‐Mbanga and Potwana’s (2006) paper in state-owned companies in South Africa, Manh Hung (2017) in Vietnam’s context found similar findings on the relationship between participation and their resistance to change. Considering Lean context, Netland (2016) and Pakdil and Leonard (2015) constantly identified employee empowerment and encouragement to participate in decision-making as vital to the success of lean programmes (especially when implementing continuous improvement) and effective when facing objections from employees, as it significantly motivates employees and increases their autonomy. 2.3.3. Training Training in this study refers to all training programs and necessary tools and knowledge provided by the organization in the initial and implementation stages of the change program (Zahra et al., 2018). As this contextual factor received limited attention from existed empirical studies in change management literature, the basis of hypothesis development would be based on the context of Lean transformation. Throughout the literature on success factors and barriers to lean implementation, employee’s expertise and knowledge are vital to the success of lean (Clegg et al., 2010; Dora et al., 2013). Thus, providing proper and timely training and education program is important to enhance employee’s skills to manage the change (Pakdil and Leonard, 2015). By being equipped with necessary tools and knowledge, employees would likely be more ready to change, leads to increased openness to change and reduced resistance to change. Also, tools and knowledge provided in training programs is viewed to be important when employees evaluating benefit-risk analysis of change initiative, as it plays a significant role in enhancing employee’s capabilities, by which, they feel less threatened by the risk of change (e.g. losing jobs when implementing lean tools), in turn, reduces resistance. 2.3.4. Trust in management Basing on Oreg (2006), trust in management is defined as the degree to which recipients are confident in the management and leadership of management levels to lead successful change, also involves the beliefs that they could rely on managers to carry out what was beneficial to the organization and employees. Throughout change management literature, studies constantly viewed trust in management as a vital antecedent to reduce recipient’ resistance to change (Cunningham et al., 2002; Kiefer, 2005). To be specific, employees perceiving their managers as being competent enough to lead the change effectively and viewing their leaders as reliable and supportive, were more likely to show supporting behaviour to the change (Wanberg and Banas, 2000; Eby et al., 2000). Oreg (2006)’s paper findings shown that a lack of trust in management significantly correlates to all three dimensions of resistance, including behavioural resistance. The study investigating in lean context also found similar results on the relationship between trust in management and resistance (Staudacher and Tantardini, 2007). 3. METHODOLOGY 3.1. Data collection Quantitative method was applied and self-reported survey data was collected. Though the method has long been questioned due to social desirability bias (Umbach, 2005), it allows researcher to study a 769
6. large number of variables (Adams et al., 2007). Also, this data collection method is appropriate since the concepts of various antecedents of RTC are well-established, defined clearly in extant literature (Oreg et al., 2011). This study conducted in a manufacturing plant in the suburb of Hanoi, in food processing industry established in 2000. The plant is implementing a large-scale organizational change, which is Lean transformation by applying one of Lean key tools – Total Productive Maintenance (TPM). The change was originally top-down from top management in headquarters to plant levels. The plant has been going through Lean transformation for four years, and achieved TPM Excellent Award from Japan Institute of Plant Maintenance earlier this year. The manufacturing plant is a successful case study in implementing Lean. By adopting a single-case design, the investigation of the sample is solely carried out within the context in which it takes place (Yin, 1984). In this study, the case study design allows researchers to collect in-depth data on resistance to change in Lean transformation case in food processing industry solely. The single-case design is also popular in change management literature, since each organizational change in each sector is different, which raises the needs of examining each case to provide insights (Vakola, 2014; Khan et al., 2017; Boohene and Williams, 2012). Also, the design is proved to be effective in rare contexts when the larger, similar set of respondents cannot be obtained; for instance, Lean implementation in Vietnam (Ishak and Bakar, 2014; Zainal, 2007). Table 1: Sample demographics A soft copy of questionnaire form via Google Doc link was sent to every worker in the manufacturing plant via internal communication networks, owing to the help of Chief Finance Officer of the manufacturing plant. Out of 200 workers in the plant, 80 (40%) responded to the questionnaire. Since the nature of TPM program involves eliminating waste via autonomous maintenance, which mostly involves machine operators, and maintenance personnel and engineers in the plant, the study attempts to maintain the equal distribution in job positions percentage, in which plant workers and engineers accounting for 55% of sample size. Detailed information on demographics of sample size is in Table 1. 770
7. 3.2. Measurement Scale items in this paper were all adopted from well-established scales in existed literature, except for training – the narrowly empirically investigated factor. All the scale items listed in Table 2 were rated on a five-point Likert scale, ranging from 1- “completely disagree” to 5 - “completely agree”. Also, items were translated into Vietnamese by researcher and tested beforehand with a group of participants. Table 2: Measurement tables Measures Author Number of items Cronbach alpha coefficients Information exchange Miller et al. (1994) 6 .79 Participation Wanberg and Banas 4 (2000) T Training Zahra et al. (2018) 4 .76 Trust in management Cook and Wall 6 (2 reversed scored .77 (1980) items) Perceived impact of change Vakola (2014) 6 (3 reversed scored .74 items) Resistance to change Oreg (2006) 5 (1 reversed scored .77 (behavioural dimension) item) 3.2. Data analysis Before making any analysis for hypothesis testing, reliability and validity of all adapted scales will be tested by Cronbach’s alpha and Exploratory Factor Analysis tests; in order to (Saunders et al., 2016). Relating to relationships between contextual antecedents and RTC, multiple regression analysis would be performed, satisfying the first research objective (Lutabingwa and Auriacombe, 2007). To test H1, H2, H3, H4 – relating to relationships between contextual antecedents and RTC, multiple regression analysis would be performed, satisfying the first research objective (Lutabingwa and Auriacombe, 2007). 4. FINDING AND DISCUSSION 4.1. Cronbach and EFA results Firstly, Cronbach alpha test was performed to test the reliability. Three scale items – a scale measuring trust in management, a scale measuring perceived impact of change and a scale measuring resistance to change – were extracted since their corrected item-total correlations are smaller than .3 (Field, 2013). Another Cronbach alpha test was performing after eliminating 3 identified items, the reported values of Cronbach coefficient alpha range from .814 for perceived impact of change to .923 for resistance to change. It demonstrated that basing on Hair et al.’s (1998) suggestion on coefficient alpha should be all higher than .60, remaining measures were assessed to have an acceptable level of reliability. Especially, the alpha reliability for the majority of measures was higher than coefficient alpha tested in original studies of well-establishing measures. 771
8. Then, EFA test (with Principle Components Analysis and Varimax Rotation) was conducted to test the validity of measures. KMO value was reported to be 0.778, also, results from Bartlett’s test shows that the p-value = .000. An expected six-factor solution was acquired from the test, with the proportion of total variance explained was 75.395%. A scale item measuring perceived impact of change was extracted as its factor loading was smaller than .05, showing that it is not qualified for factor analysis (Kim and Mueller, 1978). Table 3: Cronbach and EFA results Scale items Factor loadings Information exchange (alpha = .905) IE1 .730 IE2 .793 IE3 .798 Participation (alpha = .921) PP1 .798 PP2 .892 PP3 .872 Training (alpha = .891) TR1 .849 TR2 .758 TR3 .831 Trust in management (alpha = .894) TM1 .749 TM2 .770 TM3 .767 Perceived impact of change (alpha = .814) IC1 .758 IC2 .675 IC3 .815 Resistance to change (alpha = .923) RC1 -.767 RC2 -.848 RC3 -.735 772
9. Another EFA test was performed after extracting the identified scale, obtained KMO value this time was .79, with p-value in Bartlett’s test = .00. 76.65% of total variance was explained, all scale items were significantly loaded in their defined factors. In which, each item’s factor loadings of six identified variables were reported to be bigger than 0.6, higher than the acceptable factor loading of 0.5 (Hair et al., 1998). 4.2. Multiple regression results To test H1, H2, H3, H4 about the relationships between contextual factors and resistance to change, two regression models were carried out (M1, M2). Only M1 was found to be significant with F = 15.845, p < .01. 45.8% of total variation in resistance to change was explained by total variations in four contextual variables in Model 1. Table 4: Multiple regression results M1 M2 β (standardized) β (standardized) Independent variable Gender -.110 Age .042 Education .131 Information exchange -.231 -.245 Participation -.266 -.285 Training -.273 -.264 Trust in management -.212 -.216 R square .458 .467 Adjusted R square .429 .416 F 15.845 .419 Notes: * p < .10; p <.05; p <.01 According to regression results in Model 1, in terms of the relationships of contextual variables with resistance to change, all four contextual variables: information exchange, participation, training and trust in management were negatively correlated with resistance to change with p < .05, lending support to H1, H2, H3, H4. Also, when making comparison between absolute values of Beta standardized coefficients, the results demonstrated that among four contextual variables, training had the strongest impact, then participation, information exchange, and trust in management, respectively. Discussing the findings, H1, H2, H3, H4 received support from the data, which is consistent with previously empirical findings. When information exchange, participation and trust in management factors were re-tested in Lean transformation in the context of Vietnam and found similar findings with literature (Wanberg and Banas, 2000; Manh Hung, 2017; Jimmieson et al., 2008; Kiefer, 2005); training was an underestimated factor in extant empirical studies, however, surprisingly, the factor was found to have the biggest impact to RTC, proving its significance in explaining RTC. 773
10. 5. CONCLUSION The first four hypothesis (H1, H2, H3, H4) aiming to answer the research question, relating to the relationship between four investigated contextual factors and RTC received support from data, which means that information exchange, participation, training and trust in management are negatively correlated with RTC, in which training has the strongest impact. Organizations, especially change agents should place greater focus on providing training and education relating to organizational change to employees. Training can be referred to holding tailored training programs, providing necessary knowledge and tools, both in the initial and implementation stages of the change. By which, those training activities influence employees’ perceptions on change impact and effectively tackles resistance among employees. One of the biggest limitations of this study lies in its research design – a single-case study, which significantly restricts the generalizability and representative of the study’s findings, though the study successfully shown in-depth findings in a narrowly investigated context. Future studies should consider to study the concept of resistance to change in larger sample size, or adapting multiple-case design such as investigating RTC in two different types of changes or in different industries for a single organizational change. REFERENCES 1. Adams, J., Khan, H., Raeside, R. and White, D. (2007). Research Methods for Graduate Business and Social Science Students. Sage. 2. Al–Haddad, S. and Kotnour, T. (2015). Integrating the organizational change literature: a model for successful change. Journal of Organizational Change Management, 28(2), pp.234–262. 3. Armenakis, A. and Harris, S. (2009). Reflections: our Journey in Organizational Change Research and Practice. Journal of Change Management, 9(2), pp.127–142. 4. Ashford, S. (1988). Individual Strategies for Coping with Stress during Organizational Transitions. The Journal of Applied Behavioral Science, 24(1), pp.19–36. 5. Axtell, C., Wall, T., Stride, C., Pepper, K., Clegg, C., Gardner, P. and Bolden, R. (2002). Familiarity breeds content: The impact of exposure to change on employee openness and well–being. Journal of Occupational and Organizational Psychology, 75(2), pp.217–231. 6. Azyan, Z., Pulakanam, V. and Pons, D., 2017. Success factors and barriers to implementing lean in the printing industry: a case study and theoretical framework. Journal of Manufacturing Technology Management, 28(4). 7. Baron, R. and Kenny, D. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), pp.1173–1182. 8. Bovey, W. and Hede, A. (2001). Resistance to organizational change: the role of cognitive and affective processes. Leadership & Organization Development Journal, 22(8), pp.372–382. 9. Burnes, B. (2014). Understanding Resistance to Change – Building on Coch and French. Journal of Change Management, 15(2), pp.92–116. 10. Caldwell, S.D., Herold, D.M. and Fedor, D.B. (2004), Toward an understanding of the relationships among organizational change, individual differences, and changes in person–environment fit: a cross– level study, Journal of Applied Psychology, 89(5), pp. 868–882. 774
11. 11. Camagu, S. (2010), Investigating factors that negatively influence lean implementation in the eastern cape automotive industry, Master’s thesis, Faculty of Business and Economic Sciences, Nelson Mandela Metropolitan University, Port Elizabeth, South Africa. 12. Canning, J. and Found, P. (2015). The effect of resistance in organizational change programmes. International Journal of Quality and Service Sciences, 7(2/3), pp.274–295. 13. Carroll, B.J. (2005), 10 things a lean champion can do to lead the lean transformation, Performance Improvement Consulting, Inc. 14. Clegg, B., Rees, C. and Titchen, M. (2010), A study into the effectiveness of quality management training: a focus on tools and critical success factors, TQM Journal, Vol. 22 No. 2, pp. 188–208. 15. Coch, L. and French, J. (1948). Overcoming Resistance to Change. Human Relations, 1, pp.512–532. 16. Coetsee, L. (1999). From resistance to commitment. Public Administration Quarterly, 23, pp.204–222. 17. Cook, J. and Wall, T., 1980. New work attitude measures of trust, organizational commitment and personal need non–fulfilment. Journal of Occupational Psychology, 53(1), pp.39–52. 18. Frazier, P., Tix, A. and Barron, K. (2004). Testing Moderator and Mediator Effects in Counseling Psychology Research. Journal of Counseling Psychology, 51(1), pp.115–134. 19. Gelfand, L., Mensinger, J. and Tenhave, T., 2009. Mediation Analysis: A Retrospective Snapshot of Practice and More Recent Directions. The Journal of General Psychology, 136(2), pp.153–178. 20. Giangreco, A. and Peccei, R. (2005), The nature and antecedents of middle manager resistance to change: evidence from an Italian context, International Journal of Human Resource Management, 16(10), pp. 1812–29. 21. Guest, R., Hersey, P. and Blanchard, K., 1986. Organizational Change Through Effective Leadership. Prentice–Hall. 22. Hair, Joseph F., Anderson, Rolph E., Tatham, Ronald L. and Black, William C. (1998), Multivariate Data Analysis, 5th ed, Prentice–Hall, Inc., Upper Saddle River, New Jersey. 23. Hannan, M. and Freeman, J. (1984). Structural Inertia and Organizational Change. American Sociological Review, 49, pp.149–164. 24. Henry, T. (1990). Practical Sampling. Sage. 25. Herold, D.M., Fedor, D.B. and Caldwell, S.D. (2007), Beyond change management: a multilevel investigation of contextual and personal influences on employees’ commitment to change, Journal of Applied Psychology, 92(4), pp. 942–951. 26. Holt, D.T., Armenakis, A.A., Field, H.S. and Harris, S.G. (2007), Readiness for organizational change, Journal of Applied Behavioral Science, 43(2), pp. 232–255. 27. Huang, C. and Huang, I. (2009). Resistance to change: The effects of organizational intervention and characteristic. Review of Business Research, 9(1), pp.110–114. 28. Ishak, N. and Bakar, A., 2014. Developing Sampling Frame for Case Study: Challenges and Conditions. World Journal of Education, 4(3). 29. Jacobs, G. and Keegan, A., 2016. Ethical Considerations and Change Recipients’ Reactions: ‘It’s Not All About Me’. Journal of Business Ethics, 152(1), pp.73–90. 30. Jadhav, J., Mantha, S. and Rane, S., 2014. Exploring barriers in lean implementation. International Journal of Lean Six Sigma, 5(2), pp.122–148. 31. Jorgensen, H., Owen, L. and Heus, A. (2009). Stop improvising change management!. Strategy & Leadership, 37(2), pp.38–44. 775
12. 32. Kanter, R., Stein, B. and Jick, T., 1992. Challenge Of Organizational Change: How Companies Experience It And Leaders Guide IT. The Free Press. 33. Khan, S., Raza, S. and George, S., 2017. Resistance to Change in Organizations: A Case of General Motors and Nokia. International Journal of Research in Management, Economics and Commerce, 7(1). 34. Kiefer, T. (2005). Feeling bad: antecedents and consequences of negative emotions in ongoing change. Journal of Organizational Behavior, 26(8), pp.875–897. 35. Kim, J. O., & Mueller, C. W. (1978). Factor analysis: Statistical methods and practical issues (No. 14). Sage. 36. Kung, F., Kwok, N. and Brown, D. (2017). Are Attention Check Questions a Threat to Scale Validity?. Applied Psychology, 67(2), pp.264–283. 37. Lewin, K. (1947). Frontiers in Group Dynamics. Human Relations, 1(1), pp.5–41. 38. Lewis, J.D. and Weigert, A. (1985), Trust as a social reality, Social Forces, Vol. 63 No. 4, pp. 967–985. 39. Lewis, L. (2006), Employee perspectives on implementation communication as predictors of perceptions of success and resistance, Western Journal of Communication, 70(1), pp. 23‐46. 40. Lines, R. (2004). Influence of participation in strategic change: resistance, organizational commitment and change goal achievement. Journal of Change Management, 4(3), pp.193–215. 41. Logan, M. and Ganster, D. (2007). The Effects of Empowerment on Attitudes and Performance: The Role of Social Support and Empowerment Beliefs. Journal of Management Studies, 44, pp.1523–1550. 42. Mohanty, R.P., Yadav, O.P. and Jain, R. (2007), Implementation of lean manufacturing principles in auto industry. Vilakshan–XIMB Journal of Management, pp. 1–32. 43. Msweli–Mbanga, P. and Potwana, N. (2006). Modelling participation, resistance to change, and organisational citizenship behaviour: A South African case. South African Journal of Business Management, 37(1), pp.21–29. 44. Netland, T.H. (2016), Critical success factors for implementing lean production: the effect of contingencies, International Journal of Production Research, 54(8), pp. 2433–2448. 45. Oreg, S. (2006). Personality, context, and resistance to organizational change. European Journal of Work and Organizational Psychology, 15(1), pp.73–101. 46. Oreg, S., Vakola, M. and Armenakis, A. (2011). Change Recipients’ Reactions to Organizational Change. The Journal of Applied Behavioral Science, 47(4), pp.461–524. 47. Pakdil, F. and Leonard, K.M. (2015), The effect of organizational culture on implementing and sustaining lean processes, Journal of Manufacturing Technology Management, 26(5), pp. 725–743. 48. Piderit, S. (2000). Rethinking Resistance and Recognizing Ambivalence: A Multidimensional View of Attitudes toward an Organizational Change. The Academy of Management Review, 25(4), pp.783–94. 49. Portioli–Staudacher, A. and Tantardini, M. (2012), Investigating the main problems in implementing Lean in supply chains of service companies, International Journal of Services and Operations Management, 11(1), pp. 87–106. 50. Rucker, D., Preacher, K., Tormala, Z. and Petty, R., 2011. Mediation Analysis in Social Psychology: Current Practices and New Recommendations. Social and Personality Psychology Compass, 5(6). 51. Saunders, M., Lewis, P. and Thornhill, A. (2016). Research methods for business students. 7th ed. Pearson. 52. Staudacher, A.P. and Tantardini, M. (2007), Lean production Implementation: a survey in Italy, XI Congreso de Ingeniería de Organización International Conference on Industrial Engineering and Industrial Management, Madrid. 776
13. 53. Umbach, P. (2005). Survey Research Emerging Issues: New Directions for Institutional Research. San Francisco: Jossey–Bass. 54. Vroom, V. (1964), Work and Motivation, Wiley, New York, NY 55. Wanberg, C. and Banas, J., 2000. Predictors and outcomes of openness to changes in a reorganizing workplace. Journal of Applied Psychology, 85(1), pp.132–142. 56. Weller, S. and Bernadine, V. (2007). Attitudes towards workplace change in the Australian higher education sector: a tale of divergence and a case for reform. New Zealand Journal of Employment Relations, 32(2), pp.53–68. 57. Womack, J. and Jones, D. (2003), Lean thinking: Banish Waste and Create Wealth in Your Corporation, Free Press, New York, NY (Simon & Schuster). 58. Yin, R.K., (1984). Case Study Research: Design and Methods. Beverly Hills, Calif: Sage Publications. 777