Investigating Factors Affecting the Purchase Intention in Petroleum Stations Implementing Sustainable Practices: A Pro-Environmental Behavior Approach with a Consideration of Sustainable Initiatives Knowledge
Abstract
:1. Introduction
2. Review of the Related Literature
2.1. Pro-Environmental Planned Behavior
2.1.1. Perceived Environmental Concern
2.1.2. Attitude towards Sustainable Solutions
2.1.3. Subjective Norm
2.1.4. Perceived Behavior Control
2.1.5. Behavior Intention
2.2. Independent Variables: Sustainable Initiatives
2.2.1. Solar PV System
2.2.2. Rainwater Harvesting
2.2.3. Green Products
2.2.4. Green Roofing
2.3. Independent Variables: Economic Factors
2.3.1. Payment Incentives
2.3.2. Urbanization
2.3.3. Employment
2.3.4. Willingness to Pay
3. Methodology
3.1. Sampling Design
3.1.1. Target Population
3.1.2. Sampling Technique and Size
- Must be a Filipino citizen living in the Philippines.
- Must be 18 years old and above.
- Familiar with the specified sustainability practices and is a frequent petroleum station customer as a driver, passenger, or walk in.
- n = sample size
- N = population under study
- e = margin of error
3.2. Research Instruments
3.2.1. Questionnaire
3.2.2. Structural Equation Modelling
3.2.3. Higher-Order Construct Analysis
3.3. Pilot Data Analysis
Reliability and Validity Test
4. Results
4.1. Respondents’ Demographic Profile
4.2. Data and Model Fit Test
4.3. Structural Model Assessment
5. Discussion
5.1. Discussion of Findings
5.2. Implication of the Study
5.2.1. Theoretical Implication
5.2.2. Practical Implication
5.3. Limitations of the Study
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Saviano, M.; Barile, S.; Spohrer, J.C.; Caputo, F. A service research contribution to the global challenge of sustainability. J. Serv. Theory Pract. 2017, 27, 951–976. [Google Scholar] [CrossRef]
- Stubbs, W.; Cocklin, C. Conceptualizing a “Sustainability business model”. Organ. Environ. 2008, 21, 103–127. [Google Scholar] [CrossRef]
- Du, W.; Pan, S.L.; Zuo, M. How to balance sustainability and profitability in technology organizations: An ambidextrous perspective, Engineering Management. IEEE Trans. 2013, 60, 366–385. [Google Scholar] [CrossRef]
- Mohammed, M.U.; Musa, I.J.; Jeb, D.N. GIS-Based Analysis of the Location of Filling Stations in Metropolitan Kano against the Physical Planning Standards. Am. J. Eng. Res. (AJER) 2014, 3, 147–158. [Google Scholar]
- Ahmad, S.N.B.; Juhdi, N.; Awadz, A.S. Examination of environmental knowledge and perceived pro-environmental behavior among students of University Tun Abdul Razak, Malaysia. Int. J. Multidiscip. Thought 2010, 1, 328–342. [Google Scholar]
- Cabalu, H.; Koshy, P.; Corong, E.; Rodriguez, U.P.E.; Endriga, B.A. Modelling the impact of energy policies on the Philippine economy: Carbon tax, energy efficiency, and changes in the energy mix. Econ. Anal. Policy 2015, 48, 222–237. [Google Scholar] [CrossRef]
- Tommasetti, A.; Singer, P.; Troisi, O.; Maione, G. Extended theory of planned behavior (ETPB): Investigating customers’ perception of restaurants’ sustainability by testing a structural equation model. Sustainability 2018, 10, 2580. [Google Scholar] [CrossRef]
- Kalhoro, M.; Au Yong, H.N.; Ramendran Spr, C. Understanding the factors affecting pro-environment behavior for city rail transport usage: Territories’ empirical evidence—Malaysia. Sustainability 2021, 13, 12483. [Google Scholar] [CrossRef]
- Zia, A.; Alzahrani, M.; Alomari, A.; AlGhamdi, F. Investigating the drivers of sustainable consumption and their impact on online purchase intentions for Agricultural Products. Sustainability 2022, 14, 6563. [Google Scholar] [CrossRef]
- Nwagbara, U.; Brown, C. Communication and conflict management: Towards the rhetoric of integrative communication for sustainability in Nigeria’s oil and gas industry. Econ. Insights Trends Chall. 2014, 66, 15–23. [Google Scholar]
- Okeke, A. Towards sustainability in the global oil and gas industry: Identifying where the emphasis lies. Environ. Sustain. Indic. 2021, 12, 100145. [Google Scholar] [CrossRef]
- Mshelia, A.M.; Abdullahi, J.; Dawha, E.D. Environmental Effects of Petrol Stations at Close Proximities to Residential Buildings in Maiduguri and Jere, Borno State, Nigeria. IOSR J. Humanit. Soc. Sci. 2015, 20, 1–8. [Google Scholar]
- Manneh, M.; Kozhevnikov, M.; Chazova, T. Determinants of consumer preference for petrol consumption: The case of petrol retail in the Gambia. Int. J. Energy Prod. Manag. 2020, 5, 175–186. [Google Scholar] [CrossRef]
- Hong, K.T.; Khoo, K.L.; Naim, M.N. The influence of consumers’ patronage behavior towards petrol stations: A multigroup analysis using PLS-SEM. J. Appl. Struct. Equ. Model. 2022, 6, 1–22. [Google Scholar] [CrossRef]
- Raed, A.A.; Ahmed, A.; Abdelhamid, A. Biomimicry approach design of petrol stations with integrating renewable energy in the UAE. In WIT Transactions on the Built Environment; WIT Press: Southampton, UK, 2022. [Google Scholar] [CrossRef]
- Persada, S. Pro Environmental Planned Behavior Model to Explore the Citizens’ Participation Intention in Environmental Impact Assessment: An Evidence Case in Indonesia; National Taiwan University of Science & Technology: Taipei, Taiwan, 2016. [Google Scholar]
- Han, H.; Yoon, H.J. Hotel customers’ environmentally responsible behavioral intention: Impact of key constructs on decision in green consumerism. Int. J. Hosp. Manag. 2015, 45, 22–33. [Google Scholar] [CrossRef]
- Aman, A.H.; Harun, A.; Hussein, Z. The Influence of Environmental Knowledge and Concern on Green Purchase Intention the Role of Attitude ad a Mediating Variable British. J. Arts Soc. Sci. 2012, 7, 145–167. [Google Scholar]
- Lai, I.; Liu, Y.; Sun, X.; Zhang, H.; Xu, W. Factors influencing the behavioural intention towards Full Electric Vehicles: An empirical study in Macau. Sustainability 2015, 7, 12564–12585. [Google Scholar] [CrossRef]
- Ajzen, I. The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211. [Google Scholar] [CrossRef]
- Eagly, A.H.; Chaiken, S. The Psychology of Attitudes; Wadsworth Cengage Learning: Belmont, CA, USA, 1993. [Google Scholar]
- Chyong, H.T.; Phang, G.; Hasan, H.; Buncha, M.R. Going green: A study of consumers’ willingness to pay for green products in Kota Kinabalu. Int. J. Bus. Soc. 2006, 7, 40–54. [Google Scholar]
- Karaiskos, D.; Tzavellas, E.; Balta, G.; Paparrigopoulos, T. P02-232—Social Network Addiction: A new clinical disorder? Eur. Psychiatry 2010, 25, 855. [Google Scholar] [CrossRef]
- Jung, T.; Chung, N.; Leue, M.C. The determinants of recommendations to use augmented reality technologies: The case of a Korean theme park. Tour. Manag. 2015, 49, 75–86. [Google Scholar] [CrossRef]
- Nguyen, N.; Nguyen, H.V.; Nguyen, P.T.; Tran, V.T.; Nguyen, H.N.; Nguyen, T.M.; Cao, T.K.; Nguyen, T.H. Some key factors affecting consumers’ intentions to purchase Functional Foods: A Case Study of functional yogurts in Vietnam. Foods 2020, 9, 24. [Google Scholar] [CrossRef]
- Choi, Y.J.; Park, J.W. Investigating factors influencing the behavioral intention of online duty-free shop users. Sustainability 2020, 12, 7108. [Google Scholar] [CrossRef]
- Zhang, T.; Liu, Z.; Zheng, S.; Qu, X.; Tao, D. Predicting errors, violations, and safety participation behavior at nuclear power plants. Int. J. Environ. Res. Public Health 2019, 17, 5613. [Google Scholar] [CrossRef]
- Hua, L.; Wang, S. Antecedents of consumers’ intention to purchase energy-efficient appliances: An empirical study based on the technology acceptance model and theory of planned behavior. Sustainability 2019, 11, 2994. [Google Scholar] [CrossRef]
- Mamman, M.; Ogunbado, A.F.; Abu-Bakr, A.S. Factors influencing customer’s behavioral intention to adopt Islamic banking in Northern Nigeria: A proposed framework. J. Econ. Financ. 2016, 7, 51–55. [Google Scholar]
- Park, E.; Ohm, J.Y. Factors influencing the public intention to use renewable energy technologies in South Korea: Effects of the fukushima nuclear accident. Energy Policy 2014, 65, 198–211. [Google Scholar] [CrossRef]
- Xiao, Q.; Liu, H.; Feldman, M.W. How does trust affect acceptance of a nuclear power plant (NPP): A survey among people living with Qinshan NPP in China. PLoS ONE 2017, 12, e0187941. [Google Scholar] [CrossRef] [PubMed]
- Lim, G.H.; Jung, W.J.; Kim, T.H.; Lee, S.Y.T. The cognitive and economic value of a nuclear power plant in Korea. Nucl. Eng. Technol. 2017, 49, 609–620. [Google Scholar] [CrossRef]
- Carfora, V.; Cavallo, C.; Catellani, P.; Del Giudice, T.; Cicia, G. Why do consumers intend to purchase natural food? integrating theory of planned behavior, value-belief-norm theory, and Trust. Nutrients 2021, 13, 1904. [Google Scholar] [CrossRef]
- Qi, X.; Ploeger, A. Explaining consumers’ intentions towards purchasing Green Food in Qingdao, China: The Amendment and extension of the theory of planned behavior. Appetite 2019, 133, 414–422. [Google Scholar] [CrossRef] [PubMed]
- Rabaia, M.K.; Abdelkareem, M.A.; Sayed, E.T.; Elsaid, K.; Chae, K.J.; Wilberforce, T.; Olabi, A.G. Environmental impacts of solar energy systems: A Review. Sci. Total Environ. 2021, 754, 141989. [Google Scholar] [CrossRef] [PubMed]
- Tanveer, A.; Zeng, S.; Irfan, M.; Peng, R. Do perceived risk, perception of self-efficacy, and openness to technology matter for solar PV adoption? an application of the extended theory of planned behavior. Energies 2021, 14, 5008. [Google Scholar] [CrossRef]
- Heaslip, E.; Costello, G.J.; Lohan, J. Assessing good-practice frameworks for the development of Sustainable Energy Communities in Europe: Lessons from Denmark and Ireland. J. Sustain. Dev. Energy Water Environ. Syst. 2016, 4, 307–319. [Google Scholar] [CrossRef]
- Stocker, T.F.; Qin, D.; Plattner, G.K.; Tignor, M.M.B.; Allen, S.K.; Boschung, J.; Nauels, A.; Xia, Y.; Bex, V.; Midgley, P.M. IPCC, 2013: Climate Change The Physical Science Basis; Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; Cambridge University Press: Cambridge, UK, 2013. [Google Scholar]
- Abdulla, F.A.; Al-Shareef, A.W. Roof rainwater harvesting systems for household water supply in Jordan. Desalination 2009, 243, 195–207. [Google Scholar] [CrossRef]
- Christian Amos, C.; Rahman, A.; Mwangi Gathenya, J. Economic analysis and feasibility of rainwater harvesting systems in urban and peri-urban environments: A review of the global situation with a special focus on Australia and Kenya. Water 2016, 8, 149. [Google Scholar] [CrossRef]
- Steffen, J.; Jensen, M.; Pomeroy, C.A.; Burian, S.J. Water Supply and stormwater management benefits of residential rainwater harvesting in U.S. cities. JAWRA J. Am. Water Resour. Assoc. 2012, 49, 810–824. [Google Scholar] [CrossRef]
- Angrill, S.; Farreny, R.; Gasol, C.M.; Gabarrell, X.; Viñolas, B.; Josa, A.; Rieradevall, J. Environmental analysis of rainwater harvesting infrastructures in diffuse and compact urban models of Mediterranean climate. Int. J. Life Cycle Assess. 2012, 17, 25–42. [Google Scholar] [CrossRef]
- Dyllick, T.; Rost, Z. Towards true product sustainability. J. Clean. Prod. 2017, 162, 346–360. [Google Scholar] [CrossRef]
- Lakastos, E.S.; Nan, L.M.; Bacali, L.; Ciobanu, G.; Ciobanu, A.M.; Cioca, L.I. Consumer satisfaction towards green products: Empirical insights from Romania. Sustainability 2021, 13, 10982. [Google Scholar] [CrossRef]
- Hameed, I.; Hyder, Z.; Imran, M.; Shafiq, K. Greenwash and green purchase behavior: An environmentally sustainable perspective. Environ. Dev. Sustain. 2021, 23, 13113–13134. [Google Scholar] [CrossRef]
- Witek, L. Barriers to green products purchase–from polish consumer perspective. In Innovation Management, Entrepreneurship and Sustainability (IMES 2017); Vysoká škola ekonomická v Praze: Prague, Czech Republic, 2017; pp. 1119–1128. [Google Scholar]
- Ottman, J. Sometimes Consumers Will Pay More to Go Green. J. Int. Consum. Mark. 1992, 16, 12–120. [Google Scholar]
- Johri, L.M.; Sahasakmontri, K. Green marketing of cosmetics and toiletries in Thailand. J. Consum. Mark. 1998, 15, 265–281. [Google Scholar] [CrossRef]
- George, A.M. The Potential Carbon Offset Represented by a Green Roof. Ph.D. Thesis, University of Virginia, Charlottesville, VA, USA, 2012. [Google Scholar] [CrossRef]
- Köhler, M.; Schmidt, M.; Grimme, F.W.; Laar, M.; Gusmão, F. Urban water retention by greened roofs in temperate and tropical climate. Technol. Resour. Manag. Dev. 2001, 2, 151–162. [Google Scholar]
- Shafique, M.; Kim, R.; Rafiq, M. Green roof benefits, opportunities, and Challenges—A Review. Renew. Sustain. Energy Rev. 2018, 90, 757–773. [Google Scholar] [CrossRef]
- Oberndorfer, E.; Lundholm, J.; Bass, B.; Coffman, R.R.; Doshi, H.; Dunnett, N.; Gaffin, S.; Köhler, M.; Liu, K.K.; Rowe, B. Green roofs as urban ecosystems: Ecological structures, functions, and services. BioScience 2007, 57, 823–833. [Google Scholar] [CrossRef]
- Skumatz, L.A. Pay as you throw in the US: Implementation, impacts, and experience. Waste Manag. 2008, 28, 2778–2785. [Google Scholar] [CrossRef]
- Seacat, J.D.; Boileau, N. Demographic and community-level predictors of recycling behavior: A statewide assessment. J. Environ. Psychol. 2018, 56, 12–19. [Google Scholar] [CrossRef]
- Timlett, R.E.; Williams, I.D. Public participation and recycling performance in England: A comparison of tools for behaviour change. Resour. Conserv. Recycl. 2008, 52, 622–634. [Google Scholar] [CrossRef]
- Park, S. Factors influencing the recycling rate under the volume-based waste fee system in South Korea. Waste Manag. 2018, 74, 43–51. [Google Scholar] [CrossRef]
- Han, F.; Xie, R.; Fang, J.; Liu, Y. The effects of urban agglomeration economies on carbon emissions: Evidence from Chinese cities. J. Clean. Prod. 2018, 172, 1096–1110. [Google Scholar] [CrossRef]
- Vicente-Molina, M.A.; Fernández-Sáinz, A.; Izagirre-Olaizola, J. Environmental knowledge and other variables affecting pro-environmental behaviour: Comparison of university students from emerging and advanced countries. J. Clean. Prod. 2013, 61, 130–138. [Google Scholar] [CrossRef]
- Diekmann, A.; Franzen, A. TheWealth of Nations and Environmental Concern. Environ. Behav. 1999, 31, 540–549. [Google Scholar] [CrossRef]
- Fan, B.; Yang, W.; Han, T. Impact of Basic Public Service Level on Pro- Environmental Behavior in China. Int. Sociol. 2018, 33, 738–760. [Google Scholar] [CrossRef]
- Ones, D.S.; Wiernik, B.M.; Dilchert, S.; Klein, R. Pro-environmental behavior. Int. Encycl. Soc. Behav. Sci. 2015, 82–88. [Google Scholar] [CrossRef]
- Singh, G.; Pandey, N. The determinants of green packaging that influence buyers’ willingness to pay a price premium. Australas. Mark. J. 2018, 26, 221–230. [Google Scholar] [CrossRef]
- Hinnen, G.; Hille, S.L.; Wittmer, A. Willingness to pay for green products in air travel: Ready for take-off? Bus. Strategy Environ. 2017, 26, 197–208. [Google Scholar] [CrossRef]
- Millar, M.; Mayer, K.J. A profile of travelers who are willing to stay in environmentally friendly hotel. Hosp. Rev. 2013, 30, 5. [Google Scholar]
- Aravena, C.; Hutchinson, W.G.; Longo, A. Environmental pricing of externalities from different sources of electricity generation in Chile. Energy Econ. 2012, 34, 1214–1225. [Google Scholar] [CrossRef]
- Gelissen, J. Explaining popular support for environmental protection. Environ. Behav. 2007, 39, 392–415. [Google Scholar] [CrossRef]
- Cresswell, J.W.; Plano Clark, V.L. Designing and Conducting Mixed Method Research; Sage: Thousand Oaks, CA, USA, 2011. [Google Scholar]
- PSA. Age and Sex Distribution in the Philippine Population (2020 Census of Population and Housing). Available online: https://www.psa.gov.ph/content/age-and-sex-distribution-philippine-population-2020-census-population-and-housing (accessed on 18 March 2024).
- Fuji, S. Environmental Concern, Attitude toward Frugality, and Ease of Behavior as Determinants of Pro-Environmental Behavior Intentions. J. Environ. Psychol. 2006, 26, 262–268. [Google Scholar] [CrossRef]
- Lin, S.C.; Nadlifatin, R.; Amna, A.; Persada, S.; Razif, M. Investigating citizen behavior intention on mandatory and voluntary Pro-Environmental programs through a pro-environmental planned behavior model. Sustainability 2017, 9, 1289. [Google Scholar] [CrossRef]
- Persada, S.F.; Lin, S.C.; Nadlifatin, R.; Razif, M. Investigating the citizens’ intention level in environmental impact assessment participation through an extended theory of planned behavior model. Glob. NEST J. 2015, 17, 847–857. [Google Scholar]
- Sun, Y.; Wang, S. Understanding consumers’ intentions to purchase green products in the social media marketing context. Asia Pac. J. Mark. Logist. 2019, 32, 860–878. [Google Scholar] [CrossRef]
- Marcos, K.J.; Moersidik, S.S.; Soesilo, T.E. Extended theory of planned behavior on utilizing domestic rainwater harvesting in Bekasi, West Java, Indonesia. IOP Conf. Ser. Earth Environ. Sci. 2021, 716, 012054. [Google Scholar] [CrossRef]
- Nadeeshani, M.; Ramachandra, T.; Gunatilake, S.; Zainudeen, N. Carbon footprint of Green Roofing: A case study from Sri Lankan Construction Industry. Sustainability 2021, 13, 6745. [Google Scholar] [CrossRef]
- Mughrabi, N.; Hussein, M.F.; Alhyari, N.H. Rooftop garden in Amman residential buildings–sustainability and utilization. In Proceedings of the 1st International Congress on Engineering Technologies, Irbid, Jordan, 16–18 June 2020; CRC Press: Boca Raton, FL, USA, 2021; pp. 196–205. [Google Scholar]
- Lili, D.; Ying, Y.; Qiuhui, H.; Mengxi, L. Residents’ acceptance of using desalinated water in China based on the theory of planned behaviour (TPB). Mar. Policy 2021, 123, 104293. [Google Scholar] [CrossRef]
- Chen, C.F.; Chao, W.H. Habitual or reasoned? using the theory of planned behavior, technology acceptance model, and habit to examine switching intentions toward public transit. Transp. Res. Part F Traffic Psychol. Behav. 2011, 14, 128–137. [Google Scholar] [CrossRef]
- Ong, A.K.; Prasetyo, Y.T.; Salazar, J.M.; Erfe, J.J.; Abella, A.A.; Young, M.N.; Chuenyindee, T.; Nadlifatin, R.; Ngurah Perwira Redi, A.A. Investigating the acceptance of the reopening Bataan Nuclear Power Plant: Integrating Protection Motivation Theory and extended theory of planned behavior. Nucl. Eng. Technol. 2021, 54, 1115–1125. [Google Scholar] [CrossRef]
- Han, H.; Hsu, L.T.; Sheu, C. Application of the theory of planned behavior to Green Hotel choice: Testing the effect of environmental friendly activities. Tour. Manag. 2010, 31, 325–334. [Google Scholar] [CrossRef]
- German, J.D.; Redi, A.A.; Prasetyo, Y.T.; Persada, S.F.; Ong, A.K.; Young, M.N.; Nadlifatin, R. Choosing a package carrier during COVID-19 pandemic: An integration of pro-environmental planned behavior (PEPB) theory and Service Quality (SERVQUAL). J. Clean. Prod. 2022, 346, 131123. [Google Scholar] [CrossRef] [PubMed]
- Vicente, P.; Marques, C.; Reis, E. Willingness to pay for environmental quality: The effects of pro-environmental behavior, perceived behavior control, environmental activism, and educational level. SAGE Open 2021, 11, 215824402110252. [Google Scholar] [CrossRef]
- Soorani, F.; Ahmadvand, M. Determinants of consumers’ food management behavior: Applying and extending the theory of planned behavior. Waste Manag. 2019, 98, 151–159. [Google Scholar] [CrossRef]
- Kwak, S.Y.; Cho, W.S.; Seok, G.A.; Yoo, S.G. Intention to use Sustainable Green Logistics Platforms. Sustainability 2020, 12, 3502. [Google Scholar] [CrossRef]
- Hair, J.F.; Astrachan, C.B.; Moisescu, O.I.; Radomir, L.; Sarstedt, M.; Vaithilingam, S.; Ringle, C.M. Executing and interpreting applications of PLS-SEM: Updates for family business researchers. J. Fam. Bus. Strategy 2021, 12, 100392. [Google Scholar] [CrossRef]
- Hair, J.F. Multivariate Data Analysis: An overview. In International Encyclopedia of Statistical Science; Springer: Berlin/Heidelberg, Germany, 2011; pp. 904–907. [Google Scholar] [CrossRef]
- Hair, J.F.; Ringle, C.M. Mirror, Mirror on the Wall: A Comparative Evaluation of Composite-based Structural Equation Modeling Methods. J. Acad. Mark. Sci. 2017, 45, 616–632. [Google Scholar] [CrossRef]
- Gumasing, M.J.J.; Bayola, A.; Bugayong, S.L.; Cantona, K.R. Determining the Factors Affecting Filipinos’ Acceptance of the Use of Renewable Energies: A Pro-Environmental Planned Behavior Model. Sustainability 2023, 15, 7702. [Google Scholar] [CrossRef]
- Lin, C.Y.; Syrgabayeva, D. Mechanism of environmental concern on intention to pay more for renewable energy: Application to a developing country. Asia Pac. Manag. Rev. 2016, 21, 125–134. [Google Scholar] [CrossRef]
- Wan, C.; Shen, G.Q. Encouraging the use of urban green space: The mediating role of attitude, perceived usefulness and perceived behavioural control. Habitat Int. 2015, 50, 130–139. [Google Scholar] [CrossRef]
- Ringle, C.M.; Sarstedt, M.; Mitchell, R.; Gudergan, S.P. Partial least squares structural equation modeling in HRM research. Int. J. Hum. Resour. Manag. 2020, 31, 1617–1643. [Google Scholar] [CrossRef]
- Becker, J.M.; Klein, K.; Wetzels, M. Hierarchical latent variable models in PLS-SEM: Guidelines for using reflective-formative type models. Long Range Plan. 2012, 45, 359–394. [Google Scholar] [CrossRef]
- Garson, G.D. Partial Least Squares Regression & Structural Model; Statistical Associates Publishers: New York, NY, USA, 2016. [Google Scholar]
- Connelly, L.M. Pilot Studies. Medsurg Nurs. 2008, 17, 411–412. [Google Scholar] [PubMed]
- Ringle, C.M.; Wende, S.; Becker, J.M. SmartPLS 3; SmartPLS: Oststeinbek, Germany, 2015. [Google Scholar]
- Henseler, J.; Ringle, C.M.; Sarstedt, M. Using partial least squares path modeling in advertising research: Basic concepts and recent issues. In Handbook of Research On International Advertising; Edward Elgar Publishing: Cheltenham, UK, 2012. [Google Scholar]
- Daskalakis, S.; Mantas, J. Evaluating the impact of a service-oriented framework for healthcare interoperability. Stud. Health Technol. Inform. 2008, 136, 285. [Google Scholar]
- Hock, M.; Ringle, C.M. Local strategic networks in the software industry: An empirical analysis of the value continuum. Int. J. Knowl. Manag. Stud. 2010, 4, 132–151. [Google Scholar] [CrossRef]
- Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E. Multivariate Data Analysis; Prentice Hall: Englewood Cliffs, NJ, USA, 2014. [Google Scholar]
- Hu, L.t.; Bentler, P.M. Fit Indices in Covariance Structure Modeling: Sensitivity to Underparameterized Model Misspecification. Psychol. Methods 1998, 3, 424–453. [Google Scholar] [CrossRef]
- Zainab, A.M.; Kiran, K.; Ramayah, T.; Karim, N.H.A. Modelling drivers of Koha Open Source Library system using partial least squares structural equation modelling. Malays. J. Libr. Inf. Sci. 2019, 24, 1–22. [Google Scholar] [CrossRef]
- Arham, A.F.; Amin, L.; Mustapa, M.A.; Mahadi, Z.; Yaacob, M.; Arham, A.F.; Norizan, N.S. “To do, or not to do?”: Determinants of stakeholders’ acceptance on dengue vaccine using PLS-SEM analysis in Malaysia. BMC Public Health 2022, 22, 1574. [Google Scholar] [CrossRef]
- Shmueli, G.; Koppius, O.R. Predictive analytics in information systems research. MIS Q. 2011, 35, 553–572. [Google Scholar] [CrossRef]
- Wesley, S.C.; Lee, M.Y.; Kim, E.Y. The Role of Perceived Consumer Effectiveness and Motivational Attitude on Socially Responsible Purchasing Behavior in South Korea. J. Glob. Mark. 2012, 25, 29–44. [Google Scholar] [CrossRef]
- Suki, N.M. Green Awareness Effects on Consumers’ Purchasing Decision: Some Insights From Malaysia. IJAPS 2013, 9, 49–63. [Google Scholar]
- Bredahl, L. Determinants of consumer attitudes and purchase intentions with regard to genetically modified food—Results of a cross-national survey. J. Consum. Policy 2001, 24, 23–61. [Google Scholar] [CrossRef]
- Yuniaristanto, Y.; Dela, U.; Martha, W.; Sutopo, W.; Hisjam, M. Investigating key factors influencing purchase intention of electric motorcycle in Indonesia. Trans. Transp. Sci. 2022, 13, 54–64. [Google Scholar] [CrossRef]
- Chin, J.; Jiang, B.C.; Mufidah, I.; Persada, S.F.; Noer, B.A. The investigation of Consumers’ Behavior Intention in Using Green Skincare Products: A Pro-Environmental Behavior Model Approach. Sustainability 2018, 10, 3922. [Google Scholar] [CrossRef]
- Mufidah, I.; Jiang, B.C.; Lin, S.-C.; Chin, J.; Rachmaniati, Y.P.; Persada, S.F. Understanding the Consumers’ Behavior Intention in Using Green Ecolabel Product through Pro-Environmental Planned Behavior Model in Developing and Developed Regions: Lessons Learned from Taiwan and Indonesia. Sustainability 2018, 10, 1423. [Google Scholar] [CrossRef]
Variable | Code | Description | Expected Direction | References |
---|---|---|---|---|
Environmental Concern | EC1 | I believe that environmental issues are critical and cannot be disregarded. | + | Fuji [69] |
EC2 | I am really concerned about the state of the world’s ecology and what it means for my future, so I propose that gasoline station owners participate in the environmental impact assessment (EIA) process. | + | Lin et al. [70]; Persada et al. [71] | |
EC3 | Because humanity is severely abusing the environment, fuel station owners should participate in the environmental impact assessment (EIA) procedure. | + | Lin et al. [70]; Persada et al. [71] | |
EC4 | When humans interfere with nature, the results are often terrible. It concerns me that gasoline station owners should participate in the environmental impact assessment (EIA) process. | + | Lin et al. [70]; Persada et al. [71] | |
Green Initiatives/Sustainable Practices Knowledge | ||||
Solar PV system | SP1 | Solar PV technology is familiar to me. | + | Sun & Wang [72] |
SP2 | I frequently learn about solar PV technologies from articles or the news. | + | Sun & Wang [72] | |
SP3 | I am well-versed in solar PV technology. | + | Sun & Wang [72] | |
SP4 | I frequently see solar photovoltaic items installed in public spaces. | + | Sun & Wang [72] | |
Rainwater Harvesting | RH1 | I am familiar with rainwater harvesting. | + | Sun & Wang [72] |
RH2 | Rainwater collecting can be utilized as a secondary source of water. | + | Marcos et al. [73] | |
RH3 | Rainwater can be collected from building roofs. | + | Marcos et al. [73] | |
RH4 | I believe that the quality of rainfall in metropolitan areas is relatively low. | + | Marcos et al. [73] | |
Green Products | MS1 | I am familiar with the use of environmentally friendly building materials. | + | Sun & Wang [72] |
MS2 | I frequently hear about eco-friendly items from articles or the news. | + | Sun & Wang [72] | |
MS3 | When I go in public places, I often see buildings made of eco-friendly materials | + | Sun & Wang [72] | |
MS4 | I know that eco-friendly materials reduce heat island effect and carbon emissions | + | - | |
Green Roof | GR1 | I am familiar with green roofing system. | + | Sun & Wang [72] |
GR2 | I know that green roof reduces carbon emissions higher than concrete roofs. | + | Nadeeshani et al. [74] | |
GR3 | I know green roof can maintain lower overall roof temperature reducing cooling cost during summer. | + | Mughrabi et al. [75] | |
GR4 | I know that green roof reduces urban heat island effect. | + | Mughrabi et al. [75] | |
Attitude Towards Sustainability | ATT1 | Sustainable solutions/initiatives will help ease concerns environmentally. | + | - |
ATT2 | Companies should implement sustainable projects. | + | - | |
ATT3 | Sustainability contributes to societal changes. | + | - | |
ATT4 | I hold a supportive attitude towards implementation of sustainable solutions. | + | - | |
Subjective Norms | SN1 | My friends and colleagues are in favor of implementing sustainability measures. | + | Lili et al. [76] |
SN2 | Most essential persons in my life would encourage the implementation of sustainability measures. | + | Chen & Chao [77] | |
SN3 | Most people who have an effect on me believe that I should support petrol outlets that support sustainability measures. | + | Chen & Chao [77] | |
Perceived Behavior Control | PBC1 | I believe supporting petrol stations using sustainability measures will improve our society. | + | Ong et al. [78] |
PBC2 | It is entirely up to me to support gas stations in implementing sustainable measures. | + | Han et al. [79] | |
PBC3 | I have the resources, time, and opportunities to investigate whether a petrol station where I intend to purchase a product employs sustainability practice. | + | Han et al. [79] | |
PBC4 | I have the flexibility to select the petrol station from which I wish to purchase a product. | + | German et al. [80] | |
Economic Factors | ||||
Payment Incentives | PI1 | It is encouraging to see firms exchanging points-for-products when purchasing green products. | + | - |
PI2 | Having even small cost incentive when purchasing green products encourages to purchase more green products. | + | - | |
Urbanization | U1 | I believe that economic progress will raise public desire for environmental reform. | + | - |
U2 | I believe that with higher level of urbanization, the stronger social needs of people thus promoting pro-environmental behavior. | + | - | |
U3 | I believe that urbanization improves environmental education that promotes pro-environmental behavior. | + | - | |
Employment | E1 | I believe that the implementation of sustainability measures generates employment for people. | + | - |
E2 | I support the emergence of green jobs to address environmental sustainability needs. | + | - | |
Willingness to Pay | WTP1 | To protect the environment, I would be willing to pay substantially higher taxes. | + | Vicente et al. [81] |
WTP2 | To protect the environment, I would be willing to pay significantly higher rates for items and services in general. | + | Vicente et al. [81] | |
WTP3 | To safeguard the environment, I would be willing to tolerate a reduction in my standard of living. | + | Vicente et al. [81] | |
Behavior Intention | BI1 | I intend to purchase products from petrol stations implementing sustainability measures. | + | Soorani & Ahmadvand [82] |
BI2 | I plan to urge others to buy products from gas stations that practice sustainability. | + | Ong et al. [78] | |
BI3 | I believe that our society will overwhelmingly favor petrol outlets that employ sustainability initiatives. | + | Ong et al. [78] | |
BI4 | I hope to explain the benefits of sustainable behaviors, particularly in light of global environmental problems. | + | Kwak et al. [83] | |
BI5 | Even if there are no environmental issues, I urge that others buy from gas stations that employ sustainability initiatives. | + | Ong et al. [78] |
Construct | Cronbach’s Alpha | N of Items | Level of Reliability |
---|---|---|---|
EC | 0.871 | 4 | Excellent |
SP | 0.819 | 4 | Excellent |
RH | 0.756 | 4 | Good |
GP | 0.796 | 4 | Good |
GR | 0.935 | 4 | Excellent |
ATT | 0.927 | 4 | Excellent |
SN | 0.901 | 3 | Excellent |
PBC | 0.764 | 4 | Good |
PI | 0.845 | 3 | Excellent |
U | 0.790 | 3 | Good |
E | 0.833 | 2 | Excellent |
WTP | 0.879 | 3 | Excellent |
BI | 0.929 | 5 | Excellent |
TOTAL | 0.957 | 46 | Excellent |
Characteristics | Category | N | % |
---|---|---|---|
Gender | Female | 238 | 59.50 |
Male | 154 | 38.50 | |
Prefer not to say | 8 | 2.00 | |
Age Bracket | Generation Z | 175 | 43.75 |
Millennial | 166 | 41.50 | |
Generation X | 35 | 8.75 | |
Baby Boomers | 24 | 6.00 | |
Civil Status | Married | 108 | 27.00 |
Separated | 4 | 1.00 | |
Single | 285 | 71.25 | |
Widowed | 3 | 0.75 | |
Area of Residence | Caraga Region | 2 | 0.50 |
National Capital Region | 194 | 48.50 | |
Region 1 | 8 | 2.00 | |
Region 2 | 1 | 0.25 | |
Region 3 | 39 | 9.75 | |
Region 4A | 134 | 33.50 | |
Region 4B | 2 | 0.50 | |
Region 5 | 6 | 1.50 | |
Region 6 | 4 | 1.00 | |
Region 7 | 4 | 1.00 | |
Region 8 | 2 | 0.50 | |
Region 9 | 0 | 0.00 | |
Region 10 | 1 | 0.25 | |
Region 11 | 2 | 0.50 | |
Region 12 | 1 | 0.25 | |
Education Level | College | 258 | 64.50 |
Post-graduate | 47 | 11.75 | |
High School | 92 | 23.00 | |
Secondary | 3 | 0.75 | |
Employment | Employed | 211 | 52.75 |
Self-Employed | 54 | 13.50 | |
Unemployed | 135 | 33.75 | |
Monthly Income | Below PHP 10,957.00 | 119 | 29.75 |
PHP 10,957 to PHP 21,914 | 66 | 16.50 | |
PHP 21,914 to PHP 43,828 | 115 | 28.75 | |
PHP 43,828 to PHP 76,669 | 56 | 14.00 | |
PHP 76,669 to PHP 131,484 | 28 | 7.00 | |
PHP 131,484 to PHP 219,140 | 8 | 2.00 | |
PHP 219,140 and above | 8 | 2.00 | |
Vehicle Owner | Yes | 194 | 48.50 |
No | 206 | 51.50 |
Variables | Items | Loadings (≥0.70) | Cronbach’s Alpha (≥0.70) | Composite Reliability (≥0.70) | Average Variance Extracted (≥0.50) |
---|---|---|---|---|---|
Environmental Concern | EC1 | 0.864 | 0.916 | 0.917 | 0.799 |
EC2 | 0.916 | ||||
EC3 | 0.893 | ||||
EC4 | 0.901 | ||||
Attitude | ATT1 | 0.914 | 0.947 | 0.948 | 0.864 |
ATT2 | 0.930 | ||||
ATT3 | 0.945 | ||||
ATT4 | 0.928 | ||||
Subjective Norm | SN1 | 0.892 | 0.890 | 0.892 | 0.819 |
SN2 | 0.922 | ||||
SN3 | 0.901 | ||||
Perceived Behavioral Control | PBC1 | 0.825 | 0.754 | 0.792 | 0.569 |
PBC2 | 0.739 | ||||
PBC3 | 0.712 | ||||
PBC4 | 0.736 | ||||
Solar PV | SP1 | 0.900 | 0.817 | 0.872 | 0.726 |
SP2 | 0.888 | ||||
SP3 | 0.762 | ||||
Rainwater Harvesting | RH1 | 0.750 | 0.784 | 0.817 | 0.697 |
RH2 | 0.896 | ||||
RH3 | 0.852 | ||||
Green Roof | GR1 | 0.866 | 0.934 | 0.941 | 0.835 |
GR2 | 0.931 | ||||
GR3 | 0.933 | ||||
GR4 | 0.924 | ||||
Green Products | GP1 | 0.861 | 0.767 | 0.806 | 0.679 |
GP2 | 0.740 | ||||
GP4 | 0.864 | ||||
Employment | E1 | 0.913 | 0.813 | 0.814 | 0.842 |
E2 | 0.922 | ||||
Payment Incentives | PI1 | 0.940 | 0.863 | 0.864 | 0.880 |
PI2 | 0.936 | ||||
Urbanization | U1 | 0.903 | 0.860 | 0.873 | 0.780 |
U2 | 0.896 | ||||
U3 | 0.850 | ||||
Willingness to Pay | WTP1 | 0.868 | 0.866 | 0.882 | 0.788 |
WTP2 | 0.918 | ||||
WTP3 | 0.876 | ||||
Behavior Intention | BI1 | 0.900 | 0.919 | 0.921 | 0.757 |
BI2 | 0.889 | ||||
BI3 | 0.799 | ||||
BI4 | 0.884 | ||||
BI5 | 0.874 |
Variables | Items | Cronbach’s Alpha (≥0.70) | Composite Reliability (≥0.70) | Average Variance Extracted (≥0.50) |
---|---|---|---|---|
Sustainable Knowledge | SK | 0.754 | 0.783 | 0.575 |
Economic Factors | EF | 0.860 | 0.863 | 0.781 |
Factors | ATT | BI | E | EC | GP | GR | PBC | PI | RH | SN | SP | U | WTP |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ATT | 0.929 | ||||||||||||
BI | 0.621 | 0.87 | |||||||||||
E | 0.726 | 0.676 | 0.918 | ||||||||||
EC | 0.814 | 0.615 | 0.701 | 0.894 | |||||||||
GP | 0.488 | 0.479 | 0.48 | 0.472 | 0.824 | ||||||||
GR | 0.288 | 0.344 | 0.321 | 0.281 | 0.492 | 0.914 | |||||||
PBC | 0.617 | 0.659 | 0.647 | 0.608 | 0.528 | 0.388 | 0.754 | ||||||
PI | 0.691 | 0.7 | 0.71 | 0.688 | 0.474 | 0.37 | 0.681 | 0.938 | |||||
RH | 0.54 | 0.481 | 0.543 | 0.54 | 0.519 | 0.505 | 0.46 | 0.521 | 0.835 | ||||
SN | 0.571 | 0.625 | 0.602 | 0.572 | 0.486 | 0.301 | 0.623 | 0.604 | 0.429 | 0.905 | |||
SP | 0.26 | 0.367 | 0.307 | 0.3 | 0.336 | 0.368 | 0.379 | 0.327 | 0.38 | 0.321 | 0.852 | ||
U | 0.539 | 0.616 | 0.676 | 0.539 | 0.435 | 0.404 | 0.593 | 0.629 | 0.45 | 0.534 | 0.265 | 0.883 | |
WTP | 0.302 | 0.538 | 0.385 | 0.311 | 0.253 | 0.238 | 0.375 | 0.415 | 0.314 | 0.354 | 0.205 | 0.38 | 0.887 |
Factors | ATT | BI | E | EC | GP | GR | PBC | PI | RH | SN | SP | U | WTP |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ATT | |||||||||||||
BI | 0.662 | ||||||||||||
E | 0.825 | 0.781 | |||||||||||
EC | 0.874 | 0.667 | 0.81 | ||||||||||
GP | 0.549 | 0.557 | 0.578 | 0.541 | |||||||||
GR | 0.303 | 0.37 | 0.366 | 0.301 | 0.558 | ||||||||
PBC | 0.664 | 0.759 | 0.773 | 0.672 | 0.673 | 0.455 | |||||||
PI | 0.764 | 0.784 | 0.845 | 0.772 | 0.561 | 0.408 | 0.798 | ||||||
RH | 0.607 | 0.553 | 0.661 | 0.621 | 0.657 | 0.595 | 0.546 | 0.616 | |||||
SN | 0.622 | 0.69 | 0.707 | 0.633 | 0.574 | 0.329 | 0.732 | 0.688 | 0.509 | ||||
SP | 0.262 | 0.407 | 0.352 | 0.31 | 0.426 | 0.432 | 0.481 | 0.359 | 0.474 | 0.367 | |||
U | 0.588 | 0.687 | 0.802 | 0.599 | 0.513 | 0.448 | 0.701 | 0.724 | 0.535 | 0.602 | 0.305 | ||
WTP | 0.322 | 0.596 | 0.45 | 0.335 | 0.302 | 0.258 | 0.451 | 0.472 | 0.372 | 0.394 | 0.244 | 0.43 |
Factors | ATT | BI | EC | EF | PBC | SK | SN |
---|---|---|---|---|---|---|---|
ATT | 0.93 | ||||||
BI | 0.621 | 0.87 | |||||
EC | 0.814 | 0.615 | 0.894 | ||||
EF * | 0.743 | 0.753 | 0.73 | 0.884 | |||
PBC | 0.616 | 0.66 | 0.611 | 0.728 | 0.753 | ||
SK * | 0.539 | 0.559 | 0.546 | 0.625 | 0.587 | 0.758 | |
SN | 0.565 | 0.625 | 0.571 | 0.657 | 0.625 | 0.519 | 0.905 |
Factors | ATT | BI | EC | EF | PBC | SK | SN |
---|---|---|---|---|---|---|---|
ATT | |||||||
BI | 0.671 | ||||||
EC | 0.885 | 0.667 | |||||
EF * | 0.83 | 0.844 | 0.819 | ||||
PBC | 0.668 | 0.759 | 0.672 | 0.852 | |||
SK * | 0.617 | 0.662 | 0.631 | 0.756 | 0.746 | ||
SN | 0.623 | 0.69 | 0.633 | 0.749 | 0.732 | 0.618 |
Factors | VIF |
---|---|
ATT1 | 3.398 |
ATT2 | 3.668 |
ATT4 | 3.305 |
BI1 | 3.568 |
BI2 | 3.477 |
BI3 | 2.047 |
BI4 | 3.023 |
BI5 | 2.82 |
EC1 | 2.427 |
EC2 | 3.436 |
EC3 | 3.072 |
EC4 | 3.193 |
LVE | 2.446 |
LVGP | 1.536 |
LVGR | 1.534 |
LVPI | 2.197 |
LVRH | 1.6 |
LVSP | 1.245 |
LVU | 2.009 |
PBC1 | 1.515 |
PBC2 | 1.519 |
PBC3 | 1.68 |
PBC4 | 1.642 |
SN1 | 2.498 |
SN2 | 2.967 |
SN3 | 2.475 |
Saturated Model | Estimated Model | |
---|---|---|
SRMR | 0.074 | 0.143 |
NFI | 0.839 | 0.800 |
Paths | Direct Effect (β) | Indirect Effect (β) | Total Effects | |
---|---|---|---|---|
1 | ATT → BI | 0.079 | 0.079 | |
2 | EC → ATT | 0.740 | 0.740 | |
3 | EC → BI | 0.201 | 0.201 | |
4 | EC → PBC | 0.414 | 0.414 | |
5 | EC → SN | 0.410 | 0.410 | |
6 | EF → BI | 0.455 | 0.455 | |
7 | PBC → BI | 0.172 | 0.172 | |
8 | SK → ATT | 0.135 | 0.135 | |
9 | SK → BI | 0.408 | 0.401 | |
10 | SK → EF | 0.625 | 0.625 | |
11 | SK → PBC | 0.360 | 0.360 | |
12 | SK → SN | 0.295 | 0.295 | |
13 | SN → BI | 0.174 | 0.174 |
Paths | p-Values | Decision | |
---|---|---|---|
H1: | EC → ATT | 0.000 | Accepted |
H2: | EC → SN | 0.000 | Accepted |
H3: | EC → PBC | 0.000 | Accepted |
H4: | ATT → BI | 0.170 | Rejected |
H5: | SN → BI | 0.000 | Accepted |
H6: | PBC → BI | 0.002 | Accepted |
H7: | SK → ATT | 0.000 | Accepted |
H8: | SK → SN | 0.000 | Accepted |
H9: | SK → PBC | 0.000 | Accepted |
H10: | SK → EF | 0.000 | Accepted |
H11: | EF → BI | 0.000 | Accepted |
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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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Rebualos, R.A.A.; Prasetyo, Y.T.; Cahigas, M.M.L.; Nadlifatin, R.; Gumasing, M.J.J.; Ayuwati, I.D. Investigating Factors Affecting the Purchase Intention in Petroleum Stations Implementing Sustainable Practices: A Pro-Environmental Behavior Approach with a Consideration of Sustainable Initiatives Knowledge. Sustainability 2024, 16, 4121. https://doi.org/10.3390/su16104121
Rebualos RAA, Prasetyo YT, Cahigas MML, Nadlifatin R, Gumasing MJJ, Ayuwati ID. Investigating Factors Affecting the Purchase Intention in Petroleum Stations Implementing Sustainable Practices: A Pro-Environmental Behavior Approach with a Consideration of Sustainable Initiatives Knowledge. Sustainability. 2024; 16(10):4121. https://doi.org/10.3390/su16104121
Chicago/Turabian StyleRebualos, Rogel Angelo A., Yogi Tri Prasetyo, Maela Madel L. Cahigas, Reny Nadlifatin, Ma. Janice J. Gumasing, and Irene Dyah Ayuwati. 2024. "Investigating Factors Affecting the Purchase Intention in Petroleum Stations Implementing Sustainable Practices: A Pro-Environmental Behavior Approach with a Consideration of Sustainable Initiatives Knowledge" Sustainability 16, no. 10: 4121. https://doi.org/10.3390/su16104121