Competence and affective commitment as mediators of the effect of job characteristics on the performance of Iranian supervising engineers– supervising engineers’ perspective

[1]      S. Shahraki, E. Saghatforoush, A.Z. Ravasan, Identification and Classification of Factors Affecting the Performance of Building Supervisor Engineers for Construction Industry., J. Eng. Proj. Prod. Manag. 8 (2018).

[2]      S. Mjakuškina, M. Kavosa, I. Lapiņa, Achieving Sustainability in the Construction Supervision Process, J. Open Innov. Technol. Mark. Complex. 5 (2019) 47.

[3]      A. Salehi, P. Sadat Goosheh, Evaluating the role of supervising engineers and designers in optimizing buildings energy consumptions in line with the implementation of national building regulations, in: 3rd Natl. Conf. Clim. Build. Energy Consum. Optim. with Sustain. Dev. Approach [In Persian], 2015.

[4]      FIDIC | Quality of Construction | International Federation of Consulting Engineers, (n.d.).

[5]      M.J. Spilsbury, J. Brann, S. Norgbey, Quality of project supervision review 2009, in: Summ. Rep., Evaluation Office, Quality Assurance Section, UNEP, 2010.

[6]      D. Peterson, Safety Supervision, second ed, American Society of Safety Engineers, Des Plaines., 1999.

[7]      G. Odiorne, The new breed of supervisor: leaders in self-managed work teams, Supervision. 52 (1991) 14–17.

[8]      F. Liu, Analysis of supervision engineers’ quality, Shanxi Constr. 30 (2004) 86–87.

[9]      D. Hardison, M. Behm, M.R. Hallowell, H. Fonooni, Identifying construction supervisor competencies for effective site safety, Saf. Sci. 65 (2014) 45–53.

[10]    R.S. Maheshkumar, S.K. Purva, Impact of Supervision on Rework in Construction In, Int. J. Recent Innov. Trends Comput. Commun. 4 (2016) 1–7.

[11]    J.H. Michael, Z.G. Guo, J.K. Wiedenbeck, C.D. Ray, Production supervisor impacts on subordinates’ safety outcomes: An investigation of leader-member exchange and safety communication, J. Safety Res. 37 (2006) 469–477.

[12]    J.R. Hackman, G.R. Oldham, Development of the job diagnostic survey., J. Appl. Psychol. 60 (1975) 159.

[13]    I. Djastuti, The influence of job characteristics on job satisfaction, organizational commitment and managerial performance a study on construction companies in Central Java, Int. Res. J. Bus. Stud. 3 (2015).

[14]    L. Hsu, P. Liao, From job characteristics to job satisfaction of foreign workers in Taiwan’s construction industry: The mediating role of organizational commitment, Hum. Factors Ergon. Manuf. Serv. Ind. 26 (2016) 243–255.

[15]    K. Mostert, M. Peeters, I. Rost, Work–home interference and the relationship with job characteristics and well‐being: a South African study among employees in the construction industry, Stress Heal. 27 (2011) e238–e251.

[16]    N.A. Said, R. Munap, Job characteristics and job satisfaction: A relationship study on supervisors performance, in: 2010 IEEE Int. Conf. Manag. Innov. Technol., IEEE, 2010: pp. 714–719.

[17]    J. Johari, F.M. Shamsudin, T.F. Yean, K.K. Yahya, Z. Adnan, Job characteristics, employee well-being, and job performance of public sector employees in Malaysia, Int. J. Public Sect. Manag. (2019).

[18]    H.N. Onukwube, R. Iyagba, Construction professionals job performance and characteristics: A comparison of indigenous and expatriate construction companies in Nigeria, Australas. J. Constr. Econ. Build. 11 (2011) 71–83.

[19]    J.B. Sørensen, D.J. Phillips, Competence and commitment: employer size and entrepreneurial endurance, Ind. Corp. Chang. 20 (2011) 1277–1304. https://doi.org/10.1093/icc/dtr025.

[20]    C.-P. Lin, C.-M. Liu, H.-T. Chan, Developing job performance: mediation of occupational commitment and achievement striving with competence enhancement as a moderator, Pers. Rev. 51 (2022) 750–769. https://doi.org/10.1108/PR-04-2020-0296.

[21]    A. Grobelna, Effects of individual and job characteristics on hotel contact employees’ work engagement and their performance outcomes, Int. J. Contemp. Hosp. Manag. 31 (2019) 349–369. https://doi.org/10.1108/IJCHM-08-2017-0501.

[22]    E. Kahya, The effects of job characteristics and working conditions on job performance, Int. J. Ind. Ergon. 37 (2007) 515–523. https://doi.org/https://doi.org/10.1016/j.ergon.2007.02.006.

[23]    A. Katebi, M.H. HajiZadeh, A. Bordbar, A.M. Salehi, The Relationship Between “Job Satisfaction” and “Job Performance”: A Meta-analysis, Glob. J. Flex. Syst. Manag. (2021). https://doi.org/10.1007/s40171-021-00280-y.

[24]    J.E. Bono, T.A. Judge, Core self‐evaluations: A review of the trait and its role in job satisfaction and job performance, Eur. J. Pers. 17 (2003) S5–S18.

[25]    F.L. Schmidt, J.E. Hunter, Development of a causal model of processes determining job performance, Curr. Dir. Psychol. Sci. 1 (1992) 89–92.

[26]    T.A. Judge, A. Erez, J.E. Bono, The power of being positive: The relation between positive self-concept and job performance, Hum. Perform. 11 (1998) 167–187.

[27]    P. Folan, J. Browne, A review of performance measurement: Towards performance management, Comput. Ind. 56 (2005) 663–680.

[28]    N. Valaei, S. Jiroudi, Job satisfaction and job performance in the media industry: A synergistic application of partial least squares path modelling, Asia Pacific J. Mark. Logist. (2016).

[29]    M. Sony, N. Mekoth, The relationship between emotional intelligence, frontline employee adaptability, job satisfaction and job performance, J. Retail. Consum. Serv. 30 (2016) 20–32.

[30]    E. Fallah Tafti, H. Mosalman Yazdi, M. Javaheri, Investigating and evaluating the performance of supervising engineers and prioritizing the factors affecting it, in: 3rd Natl. Conf. Constr. Mater. New Technol. Constr. Ind. [In Persian], 2016.

[31]    N.A. Krima, G. Wood, G.F. Aouad, Z. Hatush, Assessing the performance of Libyan supervising engineers, Constr. Manag. Econ. 25 (2007) 509–518.

[32]    R.K. Purvanova, J.E. Bono, J. Dzieweczynski, Transformational leadership, job characteristics, and organizational citizenship performance, Hum. Perform. 19 (2006) 1–22.

[33]    J.R. Hackman, E.E. Lawler, Employee reactions to job characteristics., J. Appl. Psychol. 55 (1971) 259.

[34]    G.R. Oldham, Job characteristics and internal motivation: The moderating effect of interpersonal and individual variables, Hum. Relations. 29 (1976) 559–569.

[35]    P. Yuxiu, W. Kunaviktikul, P. Thungjaroenkul, Job characteristics and job performance among professional nurses in the university hospitals of people’s Republic of China, Chiang Mai Univ. J. Nat. Sci. 10 (2011) 171–180.

[36]    S. Hassan, Sources of professional employees’ job involvement: An empirical assessment in a government agency, Rev. Public Pers. Adm. 34 (2014) 356–378.

[37]    N. CUI, S.-F. XIAO, How Much does Job Autonomy Matter for Job Performance of Chinese Supervising Engineers: A Quantitative Study, East Asian J. Bus. Econ. 9 (2021) 71–82.

[38]    J. Krasman, Putting feedback‐seeking into “context”: job characteristics and feedback‐seeking behaviour, Pers. Rev. (2013).

[39]    S. Hauff, N. Richter, Power distance and its moderating role in the relationship between situational job characteristics and job satisfaction: An empirical analysis using different cultural measures, Cross Cult. Manag. 22 (2015) 68–89.

[40]    M.A. Faturochman, The job characteristics theory: A review, Bul. Psikol. UGM, December 2nd1997. (1997).

[41]    A.A. Uruthirapathy, G.G. Grant, The influence of job characteristics on IT and non-IT job professional’s turnover intentions, J. Manag. Dev. 34 (2015) 715–728.

[42]    J.R. Hackman, G.R. Oldham, Work Redesign, AddisonWesley, Reading, MA. (1980).

[43]    P. Ghosh, A. Rai, R. Chauhan, N. Gupta, A. Singh, Exploring the moderating role of context satisfaction between job characteristics and turnover intention of employees of Indian public sector banks, J. Manag. Dev. 34 (2015) 1019–1030.

[44]    E. Bacha, The relationship between transformational leadership, task performance and job characteristics, J. Manag. Dev. 33 (2014) 410–420.

[45]    A. Alsop, Perspectives on competence, Br. J. Ther. Rehabil. 8 (2001) 258–264.

[46]    P. Hager, A. Gonczi, Professions and competencies, Boundaries Adult Learn. (1996) 246–260.

[47]    M. Eraut, Concepts of competence, J. Interprof. Care. 12 (1998) 127–139. https://doi.org/10.3109/13561829809014100.

[48]    A. Gonczi, P. Hager, J. Athanasou, The development of competency-based assessment strategies for the professions, AGPS Canberra, 1993.

[49]    S. Messick, The psychology of educational measurement, ETS Res. Rep. Ser. 1984 (1984) i–55.

[50]    U. Sekaran, F.R. Wagner, Sense of competence: A cross-cultural analysis for managerial application, Gr. Organ. Stud. 5 (1980) 340–352.

[51]    J.P. Meyer, N.J. Allen, A three-component conceptualization of organizational commitment, Hum. Resour. Manag. Rev. 1 (1991) 61–89.

[52]    S. Qian, Q. Yuan, W. Niu, Z. Liu, Is job insecurity always bad? The moderating role of job embeddedness in the relationship between job insecurity and job performance, J. Manag. Organ. (2019) 1–17.

[53]    N. Ribeiro, D. Gomes, S. Kurian, Authentic leadership and performance: the mediating role of employees’ affective commitment, Soc. Responsib. J. (2018).

[54]    N.J. Allen, J.P. Meyer, Construct validation in organizational behavior research: The case of organizational commitment, in: Probl. Solut. Hum. Assess., Springer, 2000: pp. 285–314.

[55]    R.P. Settoon, N. Bennett, R.C. Liden, Social exchange in organizations: Perceived organizational support, leader–member exchange, and employee reciprocity., J. Appl. Psychol. 81 (1996) 219.

[56]    C. Vandenberghe, K. Bentein, F. Stinglhamber, Affective commitment to the organization, supervisor, and work group: Antecedents and outcomes, J. Vocat. Behav. 64 (2004) 47–71.

[57]    J.R. Hackman, Group influences on individuals in organizations., Consulting Psychologists Press, 1992.

[58]    T.S. Heffner, J.R. Rentsch, Organizational commitment and social interaction: A multiple constituencies approach, J. Vocat. Behav. 59 (2001) 471–490.

[59]    N.J. Allen, J.P. Meyer, Affective, continuance, and normative commitment to the organization: An examination of construct validity, J. Vocat. Behav. 49 (1996) 252–276.

[60]    J.P. Meyer, D.J. Stanley, L. Herscovitch, L. Topolnytsky, Affective, continuance, and normative commitment to the organization: A meta-analysis of antecedents, correlates, and consequences, J. Vocat. Behav. 61 (2002) 20–52.

[61]    A. Rego, A. Vitória, A. Magalhães, N. Ribeiro, M.P. e Cunha, Are authentic leaders associated with more virtuous, committed and potent teams?, Leadersh. Q. 24 (2013) 61–79.

[62]    A.S.D. Semedo, A.F.M. Coelho, N.M.P. Ribeiro, Effects of authentic leadership, affective commitment and job resourcefulness on employees’ creativity and individual performance, Leadersh. Organ. Dev. J. (2016).

[63]    N. Ribeiro, A.P. Duarte, R. Filipe, R. Torres de Oliveira, How authentic leadership promotes individual creativity: The mediating role of affective commitment, J. Leadersh. Organ. Stud. 27 (2020) 189–202.

[64]    M. Riketta, Attitudinal organizational commitment and job performance: a meta‐analysis, J. Organ. Behav. Int. J. Ind. Occup. Organ. Psychol. Behav. 23 (2002) 257–266.

[65]    C. Vandenberghe, K. Bentein, A. Panaccio, Affective commitment to organizations and supervisors and turnover: A role theory perspective, J. Manage. 43 (2017) 2090–2117.

[66]    A. Cooper-Hakim, C. Viswesvaran, The construct of work commitment: testing an integrative framework., Psychol. Bull. 131 (2005) 241.

[67]    J.P. Meyer, L. Herscovitch, Commitment in the workplace: Toward a general model, Hum. Resour. Manag. Rev. 11 (2001) 299–326.

[68]    S.E. Hobfoll, Social and psychological resources and adaptation, Rev. Gen. Psychol. 6 (2002) 307–324.

[69]    É. Lapointe, C. Vandenberghe, A. Panaccio, Organizational commitment, organization-based self-esteem, emotional exhaustion and turnover: A conservation of resources perspective, Hum. Relations. 64 (2011) 1609–1631.

[70]    K.-H. Schmidt, Organizational commitment: A further moderator in the relationship between work stress and strain?, Int. J. Stress Manag. 14 (2007) 26.

[71]    É. Lapointe, C. Vandenberghe, J.-S. Boudrias, Psychological contract breach, affective commitment to organization and supervisor, and newcomer adjustment: A three-wave moderated mediation model, J. Vocat. Behav. 83 (2013) 528–538.

[72]    B.J. Avolio, W.L. Gardner, F.O. Walumbwa, F. Luthans, D.R. May, Unlocking the mask: A look at the process by which authentic leaders impact follower attitudes and behaviors, Leadersh. Q. 15 (2004) 801–823.

[73]    J.E. Mathieu, D.M. Zajac, A review and meta-analysis of the antecedents, correlates, and consequences of organizational commitment., Psychol. Bull. 108 (1990) 171.

[74]    D.M. Randall, The consequences of organizational commitment: Methodological investigation, J. Organ. Behav. 11 (1990) 361–378.

[75]    A. Cohen, Career stage as a moderator of the relationships between organizational commitment and its outcomes: A meta‐analysis, J. Occup. Psychol. 64 (1991) 253–268.

[76]    J. Chen, C. Silverthorne, J. Hung, Organization communication, job stress, organizational commitment, and job performance of accounting professionals in Taiwan and America, Leadersh. Organ. Dev. J. (2006).

[77]    S. Samad, S.A. Selangor, Unraveling the organizational commitment and job performance relationship: Exploring the moderating effect of job satisfaction, Bus. Rev. 4 (2005) 79–84.

[78]    N. Ribeiro, İ. Yücel, D. Gomes, How transformational leadership predicts employees’ affective commitment and performance, Int. J. Product. Perform. Manag. (2018).

[79]    Z.A. Rashid, M. Sambasivan, J. Johari, The influence of corporate culture and organisational commitment on performance, J. Manag. Dev. (2003).

[80]    I.O. Ugboro, Organizational commitment, job redesign, employee empowerment and intent to quit among survivors of restructuring and downsizing, J. Behav. Appl. Manag. 7 (2006) 232–257.

[81]    M.S. Zargar, C. Vandenberghe, C. Marchand, A.K. Ben Ayed, Job scope, affective commitment, and turnover: The moderating role of growth need strength, J. Occup. Organ. Psychol. 87 (2014) 280–302.

[82]    S.E. Humphrey, J.D. Nahrgang, F.P. Morgeson, Integrating motivational, social, and contextual work design features: a meta-analytic summary and theoretical extension of the work design literature., J. Appl. Psychol. 92 (2007) 1332.

[83]    S. Nikou, Factors driving the adoption of smart home technology: An empirical assessment, Telemat. Informatics. 45 (2019) 101283.

[84]    A. Katebi, P. Homami, M. Najmeddin, Acceptance model of precast concrete components in building construction based on Technology Acceptance Model (TAM) and Technology, Organization, and Environment (TOE) framework, J. Build. Eng. 45 (2021) 103518. https://doi.org/https://doi.org/10.1016/j.jobe.2021.103518.

[85]    E. Almanasreh, R. Moles, T.F. Chen, Evaluation of methods used for estimating content validity, Res. Soc. Adm. Pharm. 15 (2019) 214–221.

[86]    P. Ifinedo, An empirical analysis of factors influencing Internet/e-business technologies adoption by SMEs in Canada, Int. J. Inf. Technol. Decis. Mak. 10 (2011) 731–766.

[87]    C.H. Lawshe, A quantitative approach to content validity, Pers. Psychol. 28 (1975) 563–575.

[88]    D.F. Polit, C.T. Beck, The content validity index: are you sure you know what’s being reported? Critique and recommendations, Res. Nurs. Health. 29 (2006) 489–497.

[89]    D.D. Nulty, The adequacy of response rates to online and paper surveys: what can be done?, Assess. Eval. High. Educ. 33 (2008) 301–314.

[90]    J.F. Hair Jr, G.T.M. Hult, C.M. Ringle, M. Sarstedt, A primer on partial least squares structural equation modeling (PLS-SEM), Sage publications, 2021.

[91]    J. Henseler, W.W. Chin, A comparison of approaches for the analysis of interaction effects between latent variables using partial least squares path modeling, Struct. Equ. Model. 17 (2010) 82–109.

[92]    S. Geisser, A predictive approach to the random effect model, Biometrika. 61 (1974) 101–107.

[93]    M. Stone, Cross‐validatory choice and assessment of statistical predictions, J. R. Stat. Soc. Ser. B. 36 (1974) 111–133.

[94]    C.M. Ringle, S. Wende, J.-M. Becker, SmartPLS 3, Boenningstedt SmartPLS GmbH. (2015).

[95]    F. Manzoor, L. Wei, T. Bányai, M. Nurunnabi, Q.A. Subhan, An examination of sustainable HRM practices on job performance: An application of training as a moderator, Sustainability. 11 (2019) 2263.

[96]    J.B. Thatcher, L.P. Stepina, R.J. Boyle, Turnover of information technology workers: Examining empirically the influence of attitudes, job characteristics, and external markets, J. Manag. Inf. Syst. 19 (2002) 231–261. https://doi.org/10.1080/07421222.2002.11045736.

[97]    M.G. Morris, V. Venkatesh, Job characteristics and job satisfaction: understanding the role of enterprise resource planning system implementation., Mis Q. 34 (2010).

[98]    G.M. Spreitzer, Psychological empowerment in the workplace: Dimensions, measurement, and validation, Acad. Manag. J. 38 (1995) 1442–1465.

[99]    J.P. Meyer, N.J. Allen, C.A. Smith, Commitment to organizations and occupations: Extension and test of a three-component conceptualization., J. Appl. Psychol. 78 (1993) 538.

[100]  J. Henseler, C.M. Ringle, R.R. Sinkovics, The use of partial least squares path modeling in international marketing, in: New Challenges to Int. Mark., Emerald Group Publishing Limited, 2009.

[101]  M. Tenenhaus, V.E. Vinzi, Y.-M. Chatelin, C. Lauro, PLS path modeling, Comput. Stat. Data Anal. 48 (2005) 159–205.

[102]  J.F. Hair, C.M. Ringle, M. Sarstedt, PLS-SEM: Indeed a silver bullet, J. Mark. Theory Pract. 19 (2011) 139–152.

[103]  C.M. Ringle, M. Sarstedt, R. Schlittgen, Genetic algorithm segmentation in partial least squares structural equation modeling, OR Spectr. 36 (2014) 251–276.

[104]  C.M. Ringle, M. Sarstedt, D.W. Straub, Editor’s comments: a critical look at the use of PLS-SEM in" MIS Quarterly", MIS Q. (2012) iii–xiv.

[105]  J.F. Hair, M. Sarstedt, C.M. Ringle, J.A. Mena, An assessment of the use of partial least squares structural equation modeling in marketing research, J. Acad. Mark. Sci. 40 (2012) 414–433.

[106]  C. Fornell, D.F. Larcker, Evaluating structural equation models with unobservable variables and measurement error, J. Mark. Res. 18 (1981) 39–50.

[107]  C.-Y. Lee, H.-Y. Chong, Q. Li, X. Wang, Joint contract–function effects on BIM-enabled EPC project performance, J. Constr. Eng. Manag. 146 (2020) 4020008.

[108]  J. Henseler, C.M. Ringle, M. Sarstedt, A new criterion for assessing discriminant validity in variance-based structural equation modeling, J. Acad. Mark. Sci. 43 (2015) 115–135.

[109]  W.W. Chin, The partial least squares approach to structural equation modeling, Mod. Methods Bus. Res. 295 (1998) 295–336.

[110]  J. Cohen, Statistical power analysis for the social sciences, (1988).

[111]  W.W. Chin, B.L. Marcolin, P.R. Newsted, A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study, Inf. Syst. Res. 14 (2003) 189–217.

[112]  P.M. Bentler, D.G. Bonett, Significance tests and goodness of fit in the analysis of covariance structures., Psychol. Bull. 88 (1980) 588.

[113]  T.K. Dijkstra, J. Henseler, Consistent partial least squares path modeling, MIS Q. 39 (2015) 297–316.

[114]  M. Wetzels, G. Odekerken-Schröder, C. Van Oppen, Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration, MIS Q. (2009) 177–195.

[115]  R.M. Baron, D.A. Kenny, The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations., J. Pers. Soc. Psychol. 51 (1986) 1173.

[116]  K.J. Preacher, G.J. Leonardelli, Calculation for the Sobel test: An interactive calculation tool for mediation tests, (2001).

[117]  C. Nitzl, J.L. Roldan, G. Cepeda, Mediation analysis in partial least squares path modeling: Helping researchers discuss more sophisticated models, Ind. Manag. Data Syst. (2016).

[118]  W.W. Chin, B.L. Marcolin, P.R. Newsted, A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study, in: 17th Int. Conf. Inf. Syst. Cleveland, OH., 1996.

[119]  P. Ifinedo, The moderating effects of demographic and individual characteristics on nurses’ acceptance of information systems: A canadian study, Int. J. Med. Inform. 87 (2016) 27–35.

[120]  J.F. Dawson, Moderation in management research: What, why, when, and how, J. Bus. Psychol. 29 (2014) 1–19.

[121]  P.J. Leather, Safety and accidents in the construction industry: a work design perspective, Work Stress. 1 (1987) 167–174.