Keywords

Supplier Contentment, Buying Relationship, United Arab Emirates, Supplier Viewpoint, Partial Least Squares Path Modelling.

Note

The paper is an updated and revised kind of a paper that was presented in Logistics Research Network (LRN) Conference: Enhancing Sustainability in Logistics, Transport and Supply Chain Management, University of Sheffield, United Kingdom, September 3-5, 2025, entitled ‘Supplier happiness in a purchasing relationship: A study from the perspective of UAE based suppliers’ (www.ciltuk.org.uk/LRN25).

Introduction

Supplier happiness is a contributing factor that would enable establishment of a solid buying relationship. This paper discusses the factors that contribute to supplier happiness, its impacts and management using recent research and concepts. The literature on supplier relationship stresses on team work, strategy alignment, and supplier development. But the majority of models concentrate on getting value by the buyers. This paper takes a supplier perspective of the issue and researches into the supplier happiness, which remains to be under-investigated. In the current market, supplier relationships have become the determinants of the performance of a firm. Supplier satisfaction is crucial to win-win and stable supply chain relationship. This research explores the issues of significance of supplier happiness in purchasing relationships. In the UAE, the research examines this aspect following previous research conducted by the Authors regarding Indian suppliers (Ganguly & Roy, 2021).

Literature Review

Supplier satisfaction may have an influence on the supplier performance and overall quality of the relationship (Field & Meile, 2008). Weller et al. (2021) looked at 18 buyer supplier relationships over time to demonstrate the way the satisfaction of the supplier develops. Suppliers and buyers can define satisfaction in different ways, due to such aspects as the growth of products, rules of prices, and the establishment of channels (Johnson et al., 2001). The ability to measure satisfaction is an important feature that helps to maintain long-term relationships and become a favoured customer (Meena & Sarmah, 2012). These dynamics enable the managers to make decisions on where to invest in the supplier relationships in order to enhance the performance of the supply chain. To achieve client satisfaction, Banerjee (2022) says it is important to measure the satisfaction of suppliers. Another significant component of supplier happiness is trust. According to Rungsithong & Meyer (2024), the buyers and sellers could develop trust through developing systems that foster trust. This is supported in the electrical and electronics industry in Malaysia. Besides engagement, quality, infrastructure and commitment, Jayaraman et al. (2020) discovered that sharing of confidential information was another new factor, which positively impacts supplier retention. Co-creation comes as a result of good communication, transparency, and open dialogue. Trabelsi (2024) discovered that the more value is created, through communication, in the fields of product design, marketing, logistics and in private labels. Such programs are useful in minimizing conflict, operational enhancement, and creation of sustainable supply chain. Suppliers can be happier and improve the performance of the supply chain by guaranteeing the reliability of delivery and quality of services (Banerjee, 2022). In a research on Turkey, Jordan, Egypt, and Saudi Arabia, AL-Shboul (2023) discovered that flexibility and reliability are positively and significantly related with reduction in supply risks. This enhances the supply chain of manufacturing companies particularly the small and medium one. The analysis also revealed that solid strategic alliances with reliable, certified, high-performance, and flexible suppliers can minimize possible supply threat that manufacturing companies can encounter.

Problem Description

Strong and sustainable supply chain involves the relations between a buyer and a supplier. Majority of the researches concentrate on the buyer. This paper attempts to address this gap by considering the supplier side and in relation to suppliers in the United Arab Emirates (UAE). It expands on the previous paper by the Authors where they had studied Indian suppliers (Ganguly & Roy, 2021), relying on the same concept. The hypotheses were developed as discussed in the following Sections.

Purchasing Policy and Supplier Happiness

Purchasing and supplier engagement can lead to a better performance of a firm because of good practices (Carr & Pearson, 2002). To be successful, the involvement of suppliers is important in new products. Full purchasing and supplier quality system may enhance the supplier relations and the performance. In order to have a working relationship, the buyers and suppliers must be culturally compatible (Sende et al., 2019). So, we propose:

H₁: The adherence to the fixed policy of purchase will cause suppliers to be happier.

Payment Policy and Supplier Happiness

Studies indicate that supply chain dynamics are influenced by practices in the payment. In the case of small and medium enterprises (SMEs), there might be rapid payment changes, a reduction in receivables, and a healthier financial condition (Grewal et al., 2024). It is essential to consider the interest of suppliers and customers when making the policy regarding paying companies (Kale & Meneghetti, 2014). Therefore:

H₂: Adherence to the payment policy will make suppliers happier.

Coordination and Supplier Happiness

Good coordination between the suppliers and the customers enhances quality and flexibility (Jayaram et al., 2011). Coordination, cooperation, and long-term expectations are maintained with the assistance of trust, commitment, and satisfaction (Rindell et al., 2014). Thus:

H₃: Adherence to the policies of coordination will increase the happiness of the suppliers.

Teamwork and Supplier Happiness

When companies collaborate, their performance by suppliers will be enhanced. This is enhanced with the assistance of information technology (IT) tools and shared learning (O'Connor et al., 2020). Flexibility, problem solving joint and information sharing are enhancing efficiency and effectiveness in relationships (Brito & Mariotto, 2017). So, we propose:

H₄: Cooperation increases supplier happiness.

Technology and Supplier Happiness

A collaboration between companies is also supported by IT and improves the performance of suppliers in high-tech supply chains (O'Connor et al., 2020). The external logistics and agility is also aided by IT (Paulraj & Chen, 2007). However, the enhancement in communication can only succeed when the buyers and the suppliers perceive technology risks as equal (Oosterhuis et al., 2011). Hence:

H₅: Supplier happiness is enhanced by technology and digitization.

The Research Conceptual Framework, formulated from the above hypothesis, is presented in Figure 1.

Research Design and Methodology

We validated the research conceptual framework presented in Figure 1 with partial least squares (PLS) methodology. It is valuable to know what suppliers like to be happy with to have good buying relationships. We have conducted an extensive literature review and also made discussions with supply chain experts. We then adopted the instrument of a prior study by the Authors (Ganguly & Roy, 2021) conducted on suppliers. The background profiles of the supplier firms who were recruited into our study are indicated in Table 1.

Table 1 Supplier Firms: Years in Operation and Product Categories Served
Years in Operation	Medical Equipment & Devices	Industrial & Construction Goods	Automotive Components	Laptop Parts & Accessories	Lighting Products	Food Processing Machinery
Less than 1 year	0	0	0	0	0	0
1–2 years	0	0	0	1	0	0
2–3 years	1	0	2	2	0	0
More than 3 years	5	4	10	11	3	3
Total Firms	6	4	12	14	3	3

Table 1 presents the distribution of participating supplier firms according to their years of operation and the categories of products they supply. All the participating organizations fall within the small and medium enterprise (SME) segment based in the country of United Arab Emirates (UAE).

Analysis and Results

To determine whether items in the scale were strong enough to work together and to test the construct validity of what we were measuring, we applied exploratory factor analysis methodology using Cronbach alpha (Hair et al., 2005). To test the goodness of the measures in the study and the overall goodness of the measurement model, we tested a mix of the factor analysis and the multiple regression. It was done through the method of partial least squares (PLS) (Joreskog, 1982) using the Smart PLS software. One should examine the reliability of every item, discriminant validity, and internal consistency to ensure that the measurement model is valid. Table 2 summarizes the latent constructs, their corresponding indicator variables, and the Partial Least Squares (PLS) estimation results.

Table 2 Latent Constructs, Indicator Variables and PLS Estimation
Construct/PLS Estimation	Indicator Variable	T Stat.
Coordination Policy (CO) Path Coefficient. = 0.2402 Communality = 0.6052 AVE = 0.6054 CR = 0/9241 Cronbach alpha = 0.9091	CO1: Cooperation across departments	11.22
	CO2: Ease of delivering goods at receiving unit	10.83
	CO3: Sharing of information	23.16
	CO4: Participation in decision-making processes	13.33
	CO5: Frequency of meetings with suppliers	10.85
	CO6: Variety of contract options	15.93
	CO7: Trust level between the parties	18.03
	CO8: Timely return of earnest money deposit	27.33
Cooperation (CP) Path Coefficient = 0.7044 Communality = 0.6229 AVE = 0.6239 CR = 0.9363 Cronbach alpha = 0.9239	CP1: Clarity regarding rejected materials	17.58
	CP2: Presence of a conflict resolution unit	15.57
	CP3: Documented conflict-handling procedures	26.89
	CP4: Courtesy shown by buyer firm	11.11
	CP5: Emergency responsiveness	11.33
	CP6: Financial reporting support	28.25
	CP7: Guidance to prevent disputes	13.34
	CP8: Internal cooperation among departments	14.55
	CP9: Prompt return of rejected goods	23.43
Purchasing Policy (PP) Path Coefficient = 0.2641 Communality = 0.6122 AVE = 0.6124 CR = 0.9262 Cronbach alpha = 0.9091	PP1: Clear commercial and technical terms	12.92
	PP2: Feasible delivery requests	20.08
	PP3: Guidance to minimize conflicts	16.66
	PP4: Order processing speed	13.58
	PP5: Defined process guidelines	13.61
	PP6: Timely exchange of documents	9.68
	PP7: Purchase orders issued within validity period	15.3
	PP8: Transparency in procurement procedures	22.28
Payment Policy (P) Path Coefficient = 0,0801 Communality = 0.7247 AVE = 0.7251 CR = 0.9126 Cronbach alpha = 0.8711	P1: Financial support when required	30.14
	P2: Gross payment clarity	31.91
	P3: Convenient payment schemes	37.89
	P4: On-time payment practices	11.78
Technology and Digitization (TD) Path Coefficient = -0.1798 Communality = 0.6354 AVE = 0.6351 CR = 0.9561 Cronbach alpha = 0.9511	TD1: Lower bidding cost via e-procurement	10.62
	TD2: Early supplier engagement through IT	16.73
	TD3: Exposure to modern tools	15.52
	TD4: Guidance in IT usage	16.71
	TD5: IT infrastructure for supply chain	31.79
	TD6: IT-enabled inspection support	22.91
	TD7: Financial challenges in adopting technology	33.71
	TD8: Managerial skill development for IT	17.44
	TD9: Assistance in implementing new technology	31.02
	TD10: IT security provisions	9.78
	TD11: Training in IT applications	15.22
	TD12: Manpower support for IT	19.02
	TD13: Workstation connectivity facilities	16.61
Overall Supplier Satisfaction AVE = 0.7620 CR = 0.9501 Cronbach alpha = 0.9369	O1: Cooperation O2: Coordination O3: Overall satisfaction O4: Payment O5: Purchasing O6: Technology & digitization	44.91 25.22 29.91 40.75 27.69 24.11

Cronbach alpha and composite reliability (CR) are used to check construct reliability and the threshold value is 0.7 in both cases. The degree to which the indicator variables represent the associated latent construct is ascertained by communality whose cut off point is 0.60 (Fornell et. al., 1996). Another significant dimension is the average variance extracted (AVE) which is a measure of convergent validity of the constructs a threshold of which is 0.5 (Fornell and Larcker, 1981). The above all figures are above the threshold values, and thus, the reliability as well as validity of the constructs are all established. Then structural model was reviewed and these figures are given in Table 3. Based on a look through Table 3, the test of the individual hypotheses and the level of significance of path coefficients as shown as t-statistic values. It can be noted that, four hypotheses were accepted, and one was denied (Technology and Digitization). It also shows totality of the fact that, 85.16 per cent of the variance of supplier happiness is accounted by the proposed constructs, where the R2 is 0.8516.

Table 3 Results of Structural Model Analysis (R2 = 0.8516)
Relationship Path	Original Estimate (O)	Sample Mean (M)	Std. Deviation	Std. Error	T-Statistic
Cooperation → Overall Supplier Satisfaction	0.5309	0.5258	0.1095	0.1094	4.869
Coordination → Overall Supplier Satisfaction	0.1994	0.2008	0.1055	0.1056	1.8921
Payment Policy → Overall Supplier Satisfaction	0.1292	0.1110	0.0830	0.0831	1.5579
Purchasing Policy → Overall Supplier Satisfaction	0.2019	0.2031	0.1349	0.1349	1.4982
Technology & Digitization → Overall Supplier Satisfaction	-0.0991	-0.0719	0.1292	0.1291	0.7675

A cursory look at Table 3 will lead to the following conclusions.

Supported Hypotheses:

H₁: The adherence to the fixed policy of purchase will cause suppliers to be happier.

H₂: Adherence to the payment policy will make suppliers happier.

H₃: Adherence to the policies of coordination will increase the happiness of the suppliers.

H₄: Cooperation increases supplier happiness.

Unsupported Hypothesis:

H₅: Supplier happiness is enhanced by technology and digitization.

Table 3 presents the outcomes of the structural model evaluation, indicating the relationships between predictor constructs and overall supplier satisfaction. The model explains 85.16% of the variance (R² = 0.8516).

Table 3 summarizes the hypothesis testing results from the structural model. Four relationships show positive influence on supplier satisfaction, while the effect of technology and digitization is not found to be statistically significant.

It is also evident that Cooperations influences the greatest, that is, it is very important to know what the other needs and maintain a good relationship to make a supplier happy. Second is the Purchasing Policy of the buyer, which is also significant to happiness of the suppliers. Then there is the Coordination and Payment Policies respectively. These demonstrate that the excellent coordination within the supply chain and the existence of clear rules of payments will keep a supplier happy. Amazingly, the influence of 'Technology & Digitization’' was not so significant on the happiness of the suppliers. This could be because most of the respondent supplier firms who were part of our study belonged to the small and medium sector category with perhaps limited investment and exposure in this domain. This compares to previous studies on supplier satisfaction in Indian context by Ganguly &d Roy (2021).

Discussion and Study Implications

Good relationships with suppliers are nowadays very important. The models which we used are reliable as our tests have indicated. Our findings indicate that in the case of buyer-supplier relationship, the collaboration between buyers and suppliers influences the overall well-being of the entire supply chain. Cooperation is the primary good ingredient to supplier happiness. It implies that supplier happiness depends on the ability to determine the needs of each other as well as maintain a long-term relationship. Purchasing rules, communication and payment rules also contribute to turning suppliers happy, which results in positive buying relations and buyer-supplier cooperation. This is necessary with the changing business world. The insignificance of technology and digitization is another probable reason that indicates that most of our respondents are small and medium suppliers that may not have funds to implement new technology. This is equivalent to one of the studies carried out by Bienhas and Haddud (2018). Future research may go into greater detail with these elements.

The present work reported attempts to address the research gap on supplier happiness in purchasing relationships. It emphasizes the significance of collaborative and trusting relationships between partner firms as a foundation of a sustainable buyer supplier relationship and may provide both parties with a competitive advantage. The hypothesis that was not premised is regarding technology and digitization. Perhaps this is due to the small and medium size of the firms in our study sample and the limits to funding that can influence the use of technology.

Practical implications: The research demonstrates the influence of cooperation, good policies, good communication, and coordination by the buyer firms in terms of value in a buying relationship. Buyer firm managers can employ such findings to consciously make efforts to enhance collaboration with the suppliers and make suppliers happier by targeting the identified factors.

Conclusion, Study Limitations and Scope of Future Research

The current dynamic technology environment and evolving consumer preferences have made the contentment of the supplier a significant priority in the purchasing relations of companies. As there is blending of the real and digital world, it is vital that organizations employ methods that give rise to teamwork and trust amongst suppliers, which usually tends to work to the advantage of all the parties involved. It is also necessary that companies get familiar with Industry 4.0 technologies and how they will influence buying and supply chain management (Delke et al., 2023). Good buying relationships are characterized by good communication and transparency. Transparency between the companies will enable suppliers to know the expectations and will participate in value addition jointly. E-procurement is one direction to move in this direction; Ali (2025) discovered that successful implementation of e-procurement enhances the use of resources and transforms the supply chain operations to become more competitive and sustainable. Investment on supplier relationship is therefore necessary in achieving goals of an organization. The claim that the happiness of suppliers leads to the success of a firm in the marketplace has received support from Moon et al. (2024) who stated that operational and strategic benefits pose a positive impact on financial performance and supplier relationship satisfaction enhancing the intentions to continue cooperating and working with suppliers.

The only limitation to the study is that it was carried out based on the perspective of supplier firms whereas much of the existing research are concerned about buyer firms. Due to the critical relationship between the buyer firms and the supplier firms in terms of supply chain resilience, future studies considering the perspective of both buyers and suppliers should be undertaken. The small sample size of the supplier firms in the current study and their concentration in a single country, United Arab Emirates (UAE), are also the study limitations. It would be desirable in the future to conduct wider research in other countries with larger sample sizes.

References

Ali, Q. (2025). Transforming organizational performance through e-procurement. South Asian Journal of Operations and Logistics, 4(1), 38-48.

Indexed at, Google Scholar, Cross Ref

Banerjee, T. (2022). Supplier satisfaction as a mediating effect on delivery and service: a PLS-SEM approach in India during COVID-19 pandemic. SN Computer Science, 3(2), 165.

Indexed at, Google Scholar, Cross Ref

Brito, R. P., & Miguel, P. L. (2017). Power, governance, and value in collaboration: differences between buyer and supplier perspectives. Journal of Supply Chain Management, 53(2), 61-87.

Indexed at, Google Scholar, Cross Ref

Carr, A. S., & Pearson, J. N. (2002). The impact of purchasing and supplier involvement on strategic purchasing and its impact on firm’s performance. International Journal of Operations & Production Management, 22(9), 1032-1053.

Indexed at, Google Scholar, Cross Ref

Delke, V., Schiele, H., Buchholz, W., & Kelly, S. (2023). Implementing Industry 4.0 technologies: Future roles in purchasing and supply management. Technological Forecasting and Social Change, 196, 122847.

Indexed at, Google Scholar, Cross Ref

Field, J. M., & Meile, L. C. (2008). Supplier relations and supply chain performance in financial services processes. International Journal of Operations & Production Management, 28(2), 185-206.

Indexed at, Google Scholar, Cross Ref

Fornell, C., Johnson, M. D., Anderson, E. W., Cha, J., & Bryant, B. E. (1996). The American customer satisfaction index: nature, purpose, and findings. Journal of marketing, 60(4), 7-18.

Indexed at, Google Scholar, Cross Ref

Ganguly, K. K., & Roy, S. (2021). Supplier satisfaction in buyer–supplier relationships: assessment from supplier perspective. Journal of business-to-business marketing, 28(3), 247-264.

Google Scholar

Grewal, J., Mohan, A., & Pérez‐Cavazos, G. (2024). Payment practices transparency and customer‐supplier dynamics. Journal of Accounting Research, 62(2), 635-674.

Indexed at, Google Scholar, Cross Ref

Jayaram, J., Xu, K., & Nicolae, M. (2011). The direct and contingency effects of supplier coordination and customer coordination on quality and flexibility performance. International journal of production research, 49(1), 59-85.

Google Scholar

Jayaraman, K., Arikrisnan, L., Kumar, K. M., & Kiumarsi, S. (2020). Key supplier retention for electrical and electronic industry: determinant factors. International Journal of Sustainable Strategic Management, 8(1), 24-48.

Google Scholar, Cross Ref

Johnson, C. J., Krapfel Jr, R. E., & Grimm, C. M. (2001). A contingency model of supplier-reseller satisfaction perceptions in distribution channels. Journal of Marketing Channels, 8(1-2), 65-90.

Google Scholar

Joreskog, K. G. (1982). The ML and PLS techniques for modeling with latent variables: Historical and comparative aspects. Systems under indirect observation, part I, 263-270.

Google Scholar

Kale, J. R., & Meneghetti, C. (2014). Supplier/customer considerations in corporate financial decisions. IIMB management review, 26(3), 149-155.

Indexed at, Google Scholar, Cross Ref

Meena, P. L., & Sarmah, S. P. (2012). Development of a supplier satisfaction index model. Industrial Management & Data Systems, 112(8), 1236-1254.

Indexed at, Google Scholar, Cross Ref

Moon, C., Bonn, M. A., & Cho, M. (2024). A comparison of the importance of wine supplier quality attributes for on-premise and off-premise wine retail establishments. International Journal of Contemporary Hospitality Management, 36(8), 2795-2823.

Indexed at, Google Scholar, Cross Ref

O’Connor, N., Lowry, P. B., & Treiblmaier, H. (2020). Interorganizational cooperation and supplier performance in high-technology supply chains. Heliyon, 6(3).

Indexed at, Google Scholar, Cross Ref

Oosterhuis, M., van Der Vaart, T., & Molleman, E. (2011). Perceptions of technology uncertainty and the consequences for performance in buyer-supplier relationships. International Journal of Production Research, 49(20), 6155-6173.

Google Scholar

Paulraj, A., & Chen, I. J. (2007). Strategic buyer–supplier relationships, information technology and external logistics integration. Journal of Supply Chain Management, 43(2), 2-14.

Google Scholar, Cross Ref

Rindell, A., Svensson, G., Mysen, T., & Billström, A. (2014). Satisfaction as a mediator between quality metrics in manufacturer-supplier relationships. International Journal of Business Excellence, 7(1), 16-27.

Google Scholar, Cross Ref

Rungsithong, R., & Meyer, K. E. (2024). Affect-based dimensions of trust: a study of buyer-supplier relationships in Thai manufacturing. Journal of Business & Industrial Marketing, 39(6), 1259-1281.

Indexed at, Google Scholar, Cross Ref

Trabelsi, R. E. A. (2024). Value creation through communication and co-creation: The key retailers’ perspective. Journal of Creating Value, 10(2), 286-304.

Indexed at, Google Scholar, Cross Ref

Weller, S. B., Pulles, N. J., & Zunk, B. M. (2021). The micro-processes of supplier satisfaction: a longitudinal multiple case study. Journal of Purchasing and Supply Management, 27(4), 100711.

Indexed at, Google Scholar, Cross Ref

Received: 20-Jan-2026, Manuscript No. AMSJ-26-16873; Editor assigned: 21-Jan-2026, PreQC No. AMSJ-26-16873(PQ); Reviewed: 28- Jan-2026, QC No. AMSJ-26-16873; Revised: 04-Feb-2026, Manuscript No. AMSJ-26-16873(R); Published: 11-Feb-2026