560 29 2784 6 9999 document 2784 GHRM in the Nigerian oil and gas industry Merged Data.docx application/vnd.openxmlformats-officedocument.wordprocessingml.document 5c1f30d394f1a4f038b31940f677f336 MD5 119245 2026-06-16 13:40:39 https://bordar.bournemouth.ac.uk/560/1/GHRM%20in%20the%20Nigerian%20oil%20and%20gas%20industry%20Merged%20Data.docx 560 1 1 application/vnd.openxmlformats-officedocument.wordprocessingml.document text Integrated Study One: Green Human Resource Management in the Nigerian Oil and Gas Industry: The Context and Implementation en staffonly cc_by_nd_4

GHRM in the Nigerian oil and gas industry Merged Data.docx

2028-06-12 2028-06-12 publication full_archive 2785 6 10001 document 2785 Challenges of GHRM and Employees Perceptions Merged Data.docx application/vnd.openxmlformats-officedocument.wordprocessingml.document 949072bd788bc9c50b0ac09fc56f044c MD5 91412 2026-06-16 13:44:34 https://bordar.bournemouth.ac.uk/560/2/Challenges%20of%20GHRM%20%20and%20Employees%20Perceptions%20Merged%20Data.docx 560 2 2 application/vnd.openxmlformats-officedocument.wordprocessingml.document text Integrated Study Two: The Challenges of Green Human Resource Management in the Nigerian Oil and Gas Industry: Employees' Perceptions of Implementation Challenges en staffonly cc_by_nd_4

Challenges of GHRM and Employees Perceptions Merged Data.docx

2028-06-12 2028-06-12 publication full_archive 2786 6 10003 document 2786 Enacting GHRM and Employees Perceptions Merged Data.docx application/vnd.openxmlformats-officedocument.wordprocessingml.document 19c8f85aa5d5115517be907ca6d4b2cb MD5 89913 2026-06-16 13:44:49 https://bordar.bournemouth.ac.uk/560/3/Enacting%20GHRM%20and%20Employees%20Perceptions%20Merged%20Data.docx 560 3 3 application/vnd.openxmlformats-officedocument.wordprocessingml.document text Integrated Study Three: Enacting Green Human Resource Management in the Nigerian Oil and Gas Industry: Employees’ Perceptions en staffonly cc_by_nd_4

Enacting GHRM and Employees Perceptions Merged Data.docx

2028-06-12 2028-06-12 publication full_archive 2787 2 10013 document 2787 indexcodes.txt text/plain 017f15e18faf3ef943e2437932ddba56 MD5 22729 2026-06-16 14:25:45 https://bordar.bournemouth.ac.uk/560/4/indexcodes.txt 560 4 4 text/plain other Generate index codes conversion from text to indexcodes en staffonly

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http://eprints.org/relation/isVersionOf https://bordar.bournemouth.ac.uk/id/document/2784 http://eprints.org/relation/isVolatileVersionOf https://bordar.bournemouth.ac.uk/id/document/2784 http://eprints.org/relation/isIndexCodesVersionOf https://bordar.bournemouth.ac.uk/id/document/2784 2788 2 10014 document 2788 indexcodes.txt text/plain 654f698a035fec6899e5e6c7c2431d14 MD5 16428 2026-06-16 14:25:45 https://bordar.bournemouth.ac.uk/560/5/indexcodes.txt 560 5 5 text/plain other Generate index codes conversion from text to indexcodes en staffonly

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http://eprints.org/relation/isVersionOf https://bordar.bournemouth.ac.uk/id/document/2785 http://eprints.org/relation/isVolatileVersionOf https://bordar.bournemouth.ac.uk/id/document/2785 http://eprints.org/relation/isIndexCodesVersionOf https://bordar.bournemouth.ac.uk/id/document/2785 2789 2 10015 document 2789 indexcodes.txt text/plain 7a97774646ce2354bf55f0cbfa6f2014 MD5 15227 2026-06-16 14:25:46 https://bordar.bournemouth.ac.uk/560/6/indexcodes.txt 560 6 6 text/plain other Generate index codes conversion from text to indexcodes en staffonly

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http://eprints.org/relation/isVersionOf https://bordar.bournemouth.ac.uk/id/document/2786 http://eprints.org/relation/isVolatileVersionOf https://bordar.bournemouth.ac.uk/id/document/2786 http://eprints.org/relation/isIndexCodesVersionOf https://bordar.bournemouth.ac.uk/id/document/2786 archive 8986 disk0/00/00/05/60 2026-06-16 16:09:38 2026-06-24 11:12:29 2026-06-24 11:12:29 data_collection show Aina Winifred woaina@bournemouth.ac.uk Takeda Sachiko stakeda@bournemouth.ac.uk Yang Yumei yangy@bournemouth.ac.uk pub fac_bl green human resource management, semi-structured interview, institutional theory, cognitive consistency theory, Ability-motivation-opportunity theory, Nigeria, oil and gas industry The qualitative data collected for my doctoral thesis provides the first comprehensive and contextualised understanding of the GHRM concept within the Nigerian oil and gas industry. Semi-structured interviews were employed to collect data. Semi-structured interviews provide a flexible and systematic means of gaining in-depth insights into participants’ experiences and organisational practices, making them particularly suitable for exploring complex and context-specific phenomena. The sensitivity of corporate environmental practices in Nigeria’s oil and gas industry means that candid disclosure requires a confidential and flexible approach to data collection. An interview guide was designed drawing on Rubin and Rubin’s (2005) responsive interview model. While integrating the principles of institutional theory, cognitive consistency theory, and the ability-motivation-opportunity (AMO) framework, the interview questions were structured to explore the objectives of the study, allocated across three studies which form the core sections of the integrated thesis inquiry. The questions were open-ended, allowing for a degree of openness in responses (Wengraf, 2001). A pilot phase was undertaken prior to the main interviews, serving four functions: validating the sampling strategy; necessitating adjustment of inclusion criteria; refining the interview guide; and assessing the feasibility of virtual interviews. The pilot revealed that most participants were unfamiliar with the term “Green HRM”, necessitating the rewording of the interview guide to clarify that “green” when incorporated into HRM refers to the integration of environmental policies into HR functions. Security concerns in Nigeria and the offshore location of most engineers meant that interviews were conducted virtually via Microsoft Teams, with two participants switching to Zoom. Each interview lasted 30 to 40 minutes and was transcribed verbatim for thematic analysis. 2026-01-02 published Business Strategy and the Environment 10.18746/bmth.data.00000560 Interview Data Bournemouth University bordar@bournemouth.ac.uk PHD Supervior Yang Yumei yangy@bournemouth.ac.uk This dataset comprises qualitative data collected from professionals in the Nigerian oil and gas industry, examining Green Human Resource Management (GHRM) adoption, implementation, challenges, and enactment. Participants held operational roles in environmental policy compliance and/or HRM, with a minimum of three years' work experience in the oil and gas industry. The sample comprised HR managers, HSE (Health, Safety, and Environment) professionals, and operational/field engineers. Participants were drawn from 14 companies across three organisational types: international oil companies (IOCs), indigenous companies (ICs), and a joint venture gas company (JVGC) co-owned by three IOCs and the state-owned oil company. Purposive sampling was the primary technique, complemented by snowball sampling, both non-probability approaches. Inclusion criteria were holding a role relevant to environmental policy compliance or HRM, with at least three years' organisational experience. Recruitment proceeded across three iterative phases: Phase One (Pilot) began through contacts in the Central Bank of Nigeria's Real Sector Division, who referred eligible participants via chain-referral (snowballing). This identified 27 potential participants, of whom 8 were recruited and interviewed. This phase also revealed the centrality of HSE professionals, who were subsequently added to the inclusion criteria. Phase Two (Main Recruitment) used LinkedIn after snowballing slowed. The researcher joined relevant sustainability groups to increase visibility and used LinkedIn Premium (including in-mail messaging) to reach professionals. Of 152 connection requests/messages sent, 58 were accepted, yielding 17 additional participants and bringing the cumulative total to 25 (constituting the sample for Study One, Chapter Four). These 25 came from nine companies: three IOCs (16 participants), five ICs (five participants), and one JVGC (four participants). Phase Three (Additional Recruitment) addressed underrepresentation of indigenous companies. A JISC-hosted online survey, with the Participant Information Sheet and Participant Agreement Form embedded (completion of the latter being mandatory before proceeding), was distributed via 26 further LinkedIn connection requests to engineers at indigenous companies. Of 11 who completed the survey, 5 met inclusion criteria and were recruited, bringing the total to 30 participants across 14 companies. Sample size and saturation Data saturation for Study One was reached at 25 participants, evidenced by thematic recurrence and no new insights emerging. The additional five participants (indigenous company representatives) were recruited not because saturation had failed, but to strengthen representational adequacy of indigenous companies for Studies Two and Three. Participant contribution across studies Each participant completed one interview, structured across three sections corresponding to three empirical studies. Participants P1–P25 contributed to all three studies (Chapters Four, Five, and Six); participants P26–P30 (all from indigenous companies) contributed only to Studies Two and Three. Data collection method Semi-structured, one-to-one interviews were used rather than group methods, given the sensitivity of corporate environmental disclosures, the offshore location of many engineers, and security considerations in Nigeria. An interview guide was developed iteratively with supervisors, structured around the study's three core objectives (institutional influences and the gap between formal and enacted GHRM; perceived challenges in GHRM implementation; and GHRM enactment and its perceived impact on green commitment and performance). A pilot phase preceded main data collection and led to refinements: inclusion criteria were expanded to capture HSE professionals, interview questions were reworded to clarify the meaning of "Green HRM" for participants unfamiliar with the term, and question sequencing was adjusted to move from organisational to individual-level experience. Interviews were conducted virtually (primarily via Microsoft Teams, with Zoom used for two participants who experienced technical issues), each lasting 30–40 minutes, conducted in English, and transcribed verbatim. This study received ethical approval from the Faculty of Business School and Research Committee at Bournemouth University (approval ID: 47074). Informed consent was obtained from all participants prior to data collection via a Participant Information (PI) sheet and Participant Agreement Form (PAF), which set out the research title, objectives, confidentiality arrangements, voluntary nature of participation, and the right to withdraw at any stage without giving a reason (with withdrawn data excluded from analysis). For participants recruited via the pilot and main interview phases, PI and PAF documents were distributed and returned via email or, where preferred, LinkedIn messaging. For participants recruited via the JISC online survey, PI and PAF were embedded in the survey itself, with electronic consent obtained by ticking boxes corresponding to each PAF statement; completion of all boxes was mandatory before proceeding to the recruitment form. The right to withdraw was also reiterated verbally at the start of each interview. To protect participant identity, personal identifiers were removed from interview transcripts, and pseudonyms (P1, P2, P3, etc.) were assigned in their place. No real names or other directly identifying information is retained in the dataset. Data were stored on a password-protected university network, with access restricted to the researcher and supervisory team in accordance with applicable data-protection regulations. Access may also be granted to peer reviewers on a need-to-know basis where integrated manuscripts drawn from the data are submitted for publication. No further access restrictions apply to the deposited dataset beyond the confidentiality and anonymity safeguards described above. 2023 2024