MINISTRY OF EDUCATION AND TRAINING HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION GRADUATION THESIS MAJOR: GRADUATION THESIS OF THE INDUSTRIAL MANAGEMENT THE RELATIONSHIP BETWEEN JOB CRAFTING AND JOB ENGAGEMENT IN MANUFACTURING SECTOR THE MEDIATING ROLE OF PERSON - JOB FIT INSTRUCTOR: PHAN THI THANH HIEN STUDENT: TRAN THUY DIEM NGUYEN MINH TU SKLO15179 Ho Chi Minh city, 5/2025 yore NGI ) MINISTRY OE EDUCATION AND TRAINING HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION FACULTY OF ECONOMICS GRADUATION THESIS TOPIC: THE RELATIONSHIP BETWEEN JOB CRAFTING AND JOB ENGAGEMENT IN MANUFACTURING SECTOR: THE MEDIATING ROLE OF PERSON-JOB FIT Student: Tran Thuy Diem - 21124347 Nguyen Minh Tu - 21124120 Major: Industrial Management Instructor: M.A,Phan Thi Thanh Hien THU VIEN TRUONG DHSPKT SKL, 017171 | Ho Chi Minh City, May 2025 INSTRUCTOR’S COMMENTS Ho Chi Minh City, date. Instructor Page i REVIEWER'S COMMENTS Ho Chi Minh City, date. Lecturer reviews Page ii ACKNOWLEDGEMENT First of all, we would like to express our sincere thanks to the lecturers of the Faculty of Economics - Industrial Management - Ho Chi Minh City University of Technology and Education for their guidance, support, and facilitation throughout our study and training at the university. We have gained valuable knowledge and skills that will benefit us not only in this report but also in the future.
we would like to extend our deepest gratitude to Ms. Phan Thi Thanh Hien for her enthusiastic guidance and support during the process of our thesis completion, Also.we would also like to thank the colleagues at Techtronic Industries VietNam for providing useful information during our research. we would like to wish all the teachers of Ho Chi Minh City University of Technology and Education good health and enthusiasm to achieve many successes on the path of guiding future generations of students. Ho Chi Minh City, date.
Student Tran Thuy Diem and Nguyen Minh Tu Page iii LIST OF ABBREVIATIONS AGFI Adjusted Goodness of Fit Index AVE Average Variance Extracted CB-SEM Covariance-Based Structural Equation Modeling CFA Confirmatory Factor Analysis Cri Comparative Fit Index CR Composite Reliability (EFA | Exploratory Factor Analysis Em 7 | Goodness of Fit Index F———rT |JCM | Job Characteristics Model JD-R | sob JJemands-Resources KMO Kaiser-Meyer-Olkin KPIs Key performance inidicators PAF Principal Axis Factoring P-J Person-job RMSEA Root Mean Square Error of Approximation SRMR Standardized Root Mean Square Residual Page iv LIST OF TABLES Table 2.1: Three forms of job crafting by Wrzesniewski & Dutton.3: Precedited GueshOninialte sas asso canemssnmnssncnerenanemmnsmssnanasemnasiens 26 Tablé 3.2: Questionnaire Ber Odi).3: Table of measurement scales for variables in the research model.1: Cronbach`s Alpha test results for Individual Crafting variables.2: Cronbach`s Alpha test results for Collaborative Crafting variables .3: Cronbach's Alpha test results for Person Job Fit variables .4: Cronbach`s Alpha test results for Job Engagement variables.5: EEA results for the scale for the £8CtOrs.6; Composite reliability and variance extracted for factOrs .7: Discriminant validity test table of component factOrs .------ 51 lable 4 8: Regression coefficients of direct relationships in the research model.9 Reyression coefficients of indirect relationships in the research model.10: Hypothesis Testing Summary Table .1: 8 Steps for How to Implement Job Crafting as an Employee.2: Compare Myers-Briggs Type Indicator (MBTI) and StrengthsFinder.9: LIST OF FIGURES Job Characteristics Model sisssssessssssesssssssssnsssesssensanicsssecsesconsssssssssaviuussassenses 1] The research model of Chen et al.c:sessssessssssssesssseesssseeeeseeeeseees 13 The research model of Tims et al.---cscsc<c<cscsesesessee 14 The research model of Bakker et al.-- - « s<c<xcsxsxceerscee 15 The research model of Rizwan et al.----- s55 c<c<c<ccsesex 15 The research model of Baghdadi et al.----5-55+s<s<scxss+ 16 The research model of Demerouti (2014).ccsccccessssssesessssssserscsescessessessnees 17 RESEatCh MODEL oscsessasssessssicressrsansases ‘ seed Research process Ílow chart.24 CB:SEM iImplenientalon Process wsensccnsssaccainncercasssaneszecnesssnccesonnnacnesataves 32 SUGISHEAl Chait GY GEAAEE, ccccccssasnsapnsarvxsiseseavenenroxoanineessaninaunacerseunaneseasssainses 41 Statistical Chart Hy CEPA.nsnscccaresscerssssssennesvensesssvavanesotennnnsscnrnvsanie 42 Statistical chart. by Working thie .ccccsesasersenscasevecsssassensssoenestarsnsneesa¥avse 42 CRA analysis pest tsOF tie de. cuss ensrcannesnonncenancasonnansnannansersexennennasoenons 49 SEM analysis results of the standardized research model .- 51 5 Benefits öƒ job GFiÍ[ÏHE,. Sun HH ngư 58 JOD EATING WOTKSIIOD very resresoxrrercreererommesorenntnsnenanvssinnentnneevarnconnasnepaasaasecsies 59 OnE Ob CEA RINE WER SHO ap encsnneererenemcernenerscennvenerannesneaccrnseserasacass 60 Onboarding and new hire Orientation .cssecsssceseseseereeescncsessseseeteneneneseeennees 63 Je Cee IS AEBE P IR.
«asso esc searasmecran anne eamersamnursonnenne 64 Key elements of job enrichinent.csssssssssecscssssosvenserseresecneesnenonsneneansies Deel facilitates 360-degree feedback Gallup Q12: The survey framework for effective employee engagement. HH HH rrerszererrsrseee 67 Page vi TABLE OF CONTENTS INSTRUCTOR'S COMMENTS. lìibkkoksée1lklikôk¿44649:34/04ssueloesui dA046666960630609680656 Si REVIEWER'S COMMENTS. S9646696866096568569696966 Hi LIST OF ABBREVIATIONS vesssssssssessorsessovsncsessiscosovssvens k49862446290505004108280/6348464Acsx40) eons LIST OF TABLES} ncoscsrescosesestasconscscnaicssecseavecsssyesvaonsieessisen ==.ỒỘŨ eiessssa V LIST OF FIGURES.
- vii CHAPTER 1: INTRODUCTION. De FRI OTIE. coccocssesseinnnnineneasnsnneaneernnenrmions eek 2) REGEBTCH ODOC VES. cvcsssssascsanmeusrrsasronnannnnearseanesasnaisnenesnabonencanieneaniatemasanenanaeees 2 Bu SUB RCt dnd SCOPE CETESEATOR dua cusardiiadieotldisebxsengEiiip6414991/6106404204301865g00ã 020 00 2 RESCONCIS ETO OO BY oes cceniiverirtsescunneaanennanan eonevennapeeranenmnnecaneananasapeesneneaeisaniarens 3 5.
SUCHE OF (NE EDĐTT 14 CHÍ DEN suaenvennnanininitoobittbBssapistaxettkgs6fscpsoigobssgtianosstl 4 CHAPTER 1 SUMMARY acscccssccesstsescesssesssssssssesssssesensenes m1. 5 CHAPTER 2: THEORETICAL BACKGROUND AND RESEARCH MODEL.) Ác CIB1ED COC RIN neon cernensynssarennnerettetereresren en pernen ny 0060 09080861500101559246/0100388450093886) 6 8a1x1:100 D08 trợ nh 00604000700004000018100114060010000110000001/1000110001800830000100340100860x6sexd 6 In Ke=ằắằx. ác tt HH 910191212241 5171111111111 11E1x xe re 9 2.2 Job crafLing th€OrFy.3 Summary of preViOUS StU(ÏS.4 Hypotheses development and research model .2 Research model CHAPTER 2 SUMMARY. VẾt 3 992911000010209924200499391490900900990006000000192010saÄ) 23 CHAPTER 3: RESEARCH METHODOLOGY.2 CB-SEM Method.2 Main types of variables in SIM model .3 Model evaluation process using CH-SI:M.3 Proposed preliminary SCAIC .csscserssessenssesesessssssscsecesssseeesessscssscacnracsescscerseenerees 32 Page vii 3:4 MeiEiffnenitirtiSfUHIGBE caseeeseedsoekiddaiiboolddtavaildadiatdkdAkidiïsEtsšalaxidsedssg qua 6ssả 33 3.5 SiV€ÿ triếUĐ:: se saxnoiasitrinntidiodtdadtdsgiavgd601i48641523EE64G0A8846:61818g6 813060670486 35 316: DAN ATIAIV SIS sccssscanesocnonconsniansansicassunsini dans vinnsvtsnevctsadvsonsuaveascassemumnsocannenasecddese 36 3.1 Cronbach's Alpha reliability coefficient .ccscsssssssssssssessesessseesssenesneeeseenes 36 36:2 Exploratory Factor Anal VSS sssisssswasccssvesstarssasvsnensetsvcsnsnweatvanciciancsansearancnses 37 3:63 Confiririatity Factor Anal 9 S18 (sassscssvssssvesuvanssnsweesnecanccsssceasvinscsvassesswuaiwieuseese 38 3.4 Structaral Equation: MOde ii sscsecisssassanssnsccsveviasansssswesncssvanavennsuessnnscweadewesese CHAPTER 3 SUMMARY.
s9) CHAPTER 4: RESEARCH RESULTS.1 Iescription of the research sample .M€asùtEiiieïit sEálé eVBIUBLDosseseeieooglsibsbisiG0140116300x840130n16850558/0/061311028686 Š;2.CTRRÍHE canekkiebakiistALGL642011)68614644466300210466E001460803864140,6ug0,XE 43 4;2:2°C0I bo CHỈ đổ so sse«eneiiEBAi.3:37 t0 1GB TÍÌEGueeiebenaeointrtiaooatiosavndatsaseeseetyrolesst0eGvsogrraaesenl 44 Š 2:4 10000 50GTDEf Luataiaveiondniieiit0654<00291514061A66)36646000186016)1)86426446601405526186 45 4:3 EG IGABOTY: FACTOR BTUTIS IIS» coencnacsensxsravnnsxnesovenvonsipnessxerseanessannessntannsonennnensconaesl 46 4:4 CONTTMALOFY TACAOK AALY SIS nrsseyrersesorsnresoairsvonseernsepesiansascosnouensarescusanonensiatenesssonss 48 84:1 GGnÍGTIBHGE TEŠT ca uueannnge00000111010110/6000460016614)010610891466088E2434y<46L0isuusd, 48 4.2 Reliability assessment of the scale and convergent validity test.43; DISCTUD WATE VALIGIEY LOSE sesssessnanesonersensssnoavisesvsnarnoasvarvansansivenavacenvaiersieeisanss 50 4. Testing the research model using SEM linear structural modeling. 51 4G DISCUSS corsosssesentnsnsentssccncasceseassnnssrasensseossnansusespasvicvntenisssssesansvexeszeesapesaverties 54 CHAPTER 4 SUMMARY.07001200//09400040700000004007 56 CHAPTER 5: CONCLUSION AND RECOMMENDATIONS. S1 RE 0000 TH deeaeseeeiioerreeeoibaiiordarrannssee AX9S340493909E©O.SSySneaeesl 57 S11 PROMO JOD CARING: CUILUTE: c.122 Enhancing P-J Ait SAC GIES, vecosnrarenernnsrncssnnnsonsngnsrasrosetavracsnssossassseeniucsenosesacs 61 $.3 Monitor and evaluate the impact ofjob crafting .2 Limitations of the study and fUture SLUdY.
Ác GSĂSShesccvevcc 68 CHAPTER 5 SUMMARY cccccsossovcosorescerssescecssosenseveosessosescosecscensascascscescesesntonrsonevescseoes 10 CONCLUSION uvccsscseseresessroreserssssessssasees _—- ộ»990999400490940452s5992543s4oÿ —~”ò5. 1 REFERENCES cu sseseree *4990989949000089406006968966686966980400094989898064404040866606h TE Page viii APPENDIX.e ceed Neate SG. 84 Page ix CHAPTER 1: INTRODUCTION 1, Rationale In the context of globalization and remarkable advancements in science and technology, businesses are increasingly recognizing the importance of creating a positive and sustainable work environment. The rapid development of information technology.
particularly the rise of artificial intelligence (AI), is profoundly reshaping how people work across various sectors. As Al continues to automate routine tasks, organizations are looking for ways to foster a more engaged and motivated workforce, as engaged employees are known to demonstrate higher levels of performance, innovation, and organizational commitment. One concept that has garnered significant attention in this regard is job crafling—the proactive efforts employees make to redesign their jobs in ways that align better with their interests, strengths, and values (Wreesniewski & Dutton, 2001). Previous studies have demonstrated that job crafting can lead to improved job engagement.
f or example, (Tims et al., 2014) found that employees who engage in job crafting behaviors experience greater work engagement, as their job roles become more aligned with their interests, values, and strengths. This alignment not only boosts intrinsic motivation but also fosters a sense of aulonomy, competence, and meaning in work, which are key factors in sustaining engagement (Ryan & Deci, 2000). As organizations become more aware of the importance of engagement, job crafting offers a feasible and empowering strategy to help employees find greater satisfaction and involvement in their work. While job crafting is often studied in knowledge-based industries, where employees have considerable autonomy, it has been less explored in manufacturing.
Manufacturing jobs typically involve structured tasks and production targets, which might suggest that employees have limited scope to modify their roles. However, research indicates that even in these structured settings, employees do find ways to craft their jobs, such as by streamlining processes, building stronger workplace relationships, or changing their perspective on their work (Tims et al. There is a need for research to understand how job crafting occurs in manufacturing and how it relates to job engagement. Page | Moreover, as employees engage in job crafting, they modify their tasks, relationships, or cognitive perceptions in a way that increases alignment between their personal preferences and job demands (Tims et al.
By crafting their jobs to better fit their strengths and values, employees can enhance the P-J fit (Kristof-Brown et al., 2005), which may, in turn, lead to higher levels of job engagement (Bakker & Demerouti, 2008). Therefore, P-] fit may not only be an outcome of job crafting but also a critical mediator in the relationship between job crafting and job engagement. While previous research (Tims et al., 2013) has shown a positive link between job crafting and job engagement. the mechanisms behind this connection remain unclear.
Few studies have specifically examined whether P-J fit explains how job crafting influences engagement. This study aims to fill this gap by investigating whether job crafting enhances engagement in manufacturing workers by improving their P-J fit in the manulacturing sector. where jobs are often seen as less flexible and more standardized. For the above reasons, the authors chose the topic “ The relationship between job crafting and job enyayement in manufacturing: The mediating role of person-job fit” for further exploration.
The results of this research could offer important insights for manufacturing companies aiming, to enhance worker engagement, job satisfaction, and overall productivity. Research objectives The research paper has two main objectives: e To examine the direct relationship between job crafiing and job engagement within the manufacturing sector. Understanding this relationship will help clarify how proactive changes in job design by employees can influence their level of engagement and work performance. ¢ To investigate the mediating role of P-J fit in the relationship between job crafting and job engagement.
This will provide insight into how the alignment between individual characteristics and job requirements can affect the effectiveness of job crafting efforts. Subject and scope of research Research object: The relationship between job crafting and job engagement and the mediating role of P-J fit. Scope of the study: Page 2 + Research scope: The manufacturing sector in Ho Chi Minh City. + Research period: The research data used is the data collected from January 13, 2025, to March 7, 2025.
Research methodology The study adopts a quantitative research design with a survey method suggested by (Saunders et al. The stages are: Identifying the research objectives, literature review, developing hypotheses and research model: The quantitative research process begins with identifying the research objectives. which helps clearly define the problem to be addressed and the scope of the study. The next step is the literature review, aimed at collecting and analyzing previous studies to build a solid theoretical foundation and identify research gaps.
Drawing on the findings from the literature review, the researcher then proceeds to develop hypotheses—testable assumptions that reflect expected relationships between variables and to construct a research model that illustrates these relationships. These are fundamental steps that provide direction for the subsequent stages of data collection and analysis. Group discussion to modify the measurement scales, pretest: Following the development of the research model and hypotheses, a group discussion is conducted to refine and adjust the measurement scales, ensuring that the questionnaire items are clear, relevant, and aligned with the research objectives. This collaborative step often involves experts or target respondents who provide feedback on the clarity, relevance, and wording of items.