Measuring Created Value for Suppliers and Buyers: A Decision Matrix Approach—Evidence from Slovak Enterprises

Abstract

This study introduces a structured approach for assessing value creation in supplier–buyer relationships by evaluating key value-creation indicators. Recognising strategic collaboration in B2B, the research focuses on identifying key indicators and determining their relevance based on Slovak manufacturing enterprises. Empirical data were collected via questionnaires distributed to manufacturing firms across Slovakia. Based on these data, a decision matrix was developed to quantify the value provided to suppliers and buyers. Results reveal that suppliers prioritise financial reliability and adherence to business terms, while buyers place higher value on service-related attributes such as maintenance and product quality updates. The proposed matrix serves as a practical tool for enterprises seeking to evaluate and enhance their stakeholder relationships. By offering quantifiable insights, the study supports more effective decision-making in supply chain and relationship management.

1. Introduction

Enterprises are increasingly focusing on creating value for their stakeholders beyond just shareholders. This strategic shift reflects the growing consensus that stakeholder engagement is essential for long-term business success, sustainability, and resilience (Harrison & Wicks, 2013). Modern enterprises understand that stakeholders include not only owners and customers but also suppliers, employees, and strategic partners, and that fostering open and sustainable relationships with them is a key source of competitive advantage (Freudenreich et al., 2020; Freeman et al., 2021). In the B2B sector, these stakeholders include suppliers and buyers. A recent report by State of Flux (2024) emphasized the strategic importance of business partner relationships and the need to maximize returns from these interactions. As highlighted by State of Flux (2024), “No organisation is completely independent; each forms part of an interconnected web.” This underscores the increasing importance of understanding inter-organisational relationships and value creation across supply chains. According to State of Flux (2023), 71% of enterprises define “return on relationships” as the creation of value extending beyond mere financial transactions. This highlights the need to focus not only on financial value but also on broader benefits for suppliers and buyers. Furthermore, 70% of enterprises intend to shift from transactional to strategic relationships to enhance returns, reflecting a growing emphasis on long-term value (State of Flux, 2023). The State of Flux (2022) report notes that 73.5% of enterprises experience increased trust in collaborative partnerships, reinforcing the value of closer supplier engagement. Additionally, 79% of firms believe that viewing suppliers as extensions of the enterprise significantly mitigates operational risk (State of Flux, 2023). Reducing risk is yet another key reason for enterprises to collaborate closely with their strategic suppliers and buyers.

The value-creation process plays a critical role in strengthening supplier–buyer relationships. It involves not only delivering financial value but also promoting collaboration, trust, and mutual adaptation (Grönroos & Helle, 2010; Yang & Leposky, 2022). Identifying and evaluating value-creation indicators allows firms to align with stakeholder expectations and improve the quality of business relationships (Tescari & Brito, 2016; Storbacka et al., 2012; Nenonen & Storbacka, 2010). Through measuring the value provided, an enterprise can evaluate whether it is delivering what its suppliers and buyers consider important and, consequently, whether it has the potential to enhance the value offered to these business partners.

To address these issues, this study conducted empirical research focused on Slovak manufacturing enterprises in the B2B sector. The primary components of the research include the following:

Identification of value-creation indicators for suppliers and buyers.

Assignment of importance to these value-creation indicators based on empirical research.

Development of a decision matrix for measuring the value created for suppliers and buyers.

Understanding the needs of business partners is a crucial aspect of building long-lasting, mutually beneficial relationships, trust, and collaboration. This can be achieved through the value-creation process. However, in order to create value for stakeholders, it is essential first to identify the value-creation indicators and assess their significance for the suppliers and buyers themselves.

The research addresses the following key issues:

The lack of identification of individual value-creation indicators provided to suppliers and buyers.

The absence of a determination regarding the importance of these value-creation indicators, as perceived by suppliers and buyers.

The absence of a method for integrating this information into a comprehensive framework for measuring value for suppliers and buyers.

The paper aims to address the identified gaps by providing a comprehensive analysis of a specific aspect of the value-creation process. Specifically, it focuses on the identification of value-creation indicators for suppliers and buyers, the determination of their importance, and the development of a method to measure the created value. This analysis is supported by a review of the relevant literature and empirical evidence, as discussed in Section 4—Results.

By addressing these challenges, the paper provides actionable recommendations for enterprises and introduces a structured, empirically validated framework—the decision matrix—for measuring the value created for suppliers and buyers. This tool enables businesses to assess their stakeholder relationships based on clearly defined value-creation indicators and their relative importance.

2. Theoretical Framework

2.1. Value Creation in Supplier–Buyer Relationships

Value creation in business-to-business (B2B) relationships is a widely studied topic, with numerous studies emphasising its role in gaining competitive advantage and ensuring long-term business sustainability (Grönroos & Helle, 2010; Eggert et al., 2018). Theories of value creation suggest that it extends beyond price and cost efficiency to encompass relationship quality, service enhancements, and innovation (Walter et al., 2001). Johnston et al. (2025) emphasised that value for buyers is generated through reliable service, tailored products, and strong post-sale support. Conversely, buyers contribute by ensuring stable demand, timely payments, and strategic partnerships (Eggert et al., 2018). Every enterprise seeks not only to maintain but also to increase its competitiveness in the market, along with its productivity and efficiency (Kucharcikova et al., 2023).

Long-term collaboration between an enterprise and its suppliers facilitates information exchange, enables thorough monitoring of the production process, and supports the development of new ideas for product or service improvement (Nguyen et al., 2020). Zeng (2020) identified key distinguishing factors in relationship-building that businesses should prioritise. These include the status of the mutual relationship, trade volume, organisational investments, commitment, trust, harmonisation, and communication.

One of the fundamental indicators of a long-term mutual relationship is trust, which, according to Korsgaard et al. (2018), evolves over time as the relationship matures. Establishing long-term relationships brings advantages to both parties—the enterprise and its business partners (Jaaskelainen, 2021). Enterprises can no longer expect suppliers to take sole responsibility for development and initiative, as was previously common, by merely ensuring supply fulfilment (Krause & Ellram, 1997). It is crucial that both parties—suppliers and buyers—experience satisfaction, as mutual satisfaction is one of the primary factors influencing the longevity of business partnerships (Vos et al., 2016; Schiele et al., 2012).

Vargo et al. (2008) argue that value co-creation is the only way value can be generated. Thus, value creation can only be achieved through the integration of various parties and their resources. Grönroos (2011) identifies two possible types of value-creation processes: co-creation of value and joint resource integration, and independent value creation (Hayslip et al., 2013).

In Slovak enterprises, value creation is increasingly recognised as a key determinant of supply chain performance. Recent studies indicate that enterprises focusing on collaborative value generation demonstrate greater resilience in fluctuating market conditions. The shift from transactional to relational approaches in supplier–buyer interactions is also a growing trend, aligning with global supply chain management practices (Christopher, 2016).

2.2. Measuring Value Creation: Approaches and Methodologies

Traditional frameworks often view value creation as a linear process based on internal resources, market position, or specific strategic actions (Bouncken et al., 2024). Assessing value creation in B2B settings remains complex due to its multidimensional nature. Traditional financial metrics, such as cost reduction and revenue growth, do not reflect intangible factors like trust, information sharing, or service quality (Lindgreen & Wynstra, 2005). Several models have been proposed to quantify value creation, including the value hierarchy model (Anderson et al., 2008), the relationship value model (Eggert et al., 2018), and customer-perceived value scales.

Decision matrix methodologies, as utilised in this study, offer a structured and quantifiable approach to evaluating supplier–buyer relationships. Similar approaches have been applied in procurement and supplier selection (De Boer et al., 2001), demonstrating their effectiveness in prioritising key value indicators. Moreover, multi-criteria decision-making (MCDM) techniques, such as the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), have been widely used for supplier evaluation (Ho et al., 2010).

The Decision Matrix Method (DMM) was selected for this study because it is simple to use and fits situations where expert input or resources are limited. Unlike the Analytical Hierarchy Process (AHP), which requires complex pairwise comparisons and consistency checks, DMM allows decision-makers to assign scores and weights directly to alternatives, making it particularly accessible for small and medium-sized enterprises (SMEs) (Ho et al., 2010). In contrast to TOPSIS, which involves normalisation and distance calculations from an ideal solution, DMM provides a more straightforward and interpretable outcome (C. Wang et al., 2020). Moreover, it supports both subjective and objective evaluations, allowing managers to combine qualitative and quantitative data (Zeiller & Edlinger, 2008). Its flexibility makes it ideal for stakeholder-related contexts where simplicity, transparency, and quick application are necessary (Lopes & Rodriguez-Lopez, 2021). As highlighted in comparative MCDM research, DMM balances methodological accuracy with ease of use, particularly when prioritising decision clarity and implementation feasibility (Aruldoss et al., 2013).

To measure value, an enterprise can employ the Decision Matrix Method (DMM). This method falls within the category of visualisation techniques, providing managers with a broad array of tools to support strategic decision-making (Zeiller & Edlinger, 2008). Decision-making methods represent a set of rules and procedures that assist businesses in making informed decisions in various contexts, such as selecting the most suitable alternative (Kmetík et al., 2019).

In the case of the Decision Matrix Method, decisions are based on both the personal preferences and opinions of the decision-maker, as well as on objective judgment and reality (Kmetík et al., 2019). Máca and Leitner (2002) describe a variant of this method involving the evaluation of individual criteria using a point scale from 1 to 10, where 1 represents the lowest weight and 10 the highest. The same scoring method may be applied to assess alternative solutions. The final and optimal decision outcome is determined by calculating the highest total sum of the products of each criterion’s evaluation and its assigned weight.

The digital transition enables the adoption of sustainable practices by reshaping business models and enhancing dynamic capabilities, thereby fostering the creation of lasting and responsible value (Ciampi et al., 2021; Leso et al., 2023). Digital transformation (DT) plays a significant role in the process of measuring value creation. It directly influences organisational competitiveness, reshapes value creation, and necessitates adaptation across industries (Gouveia et al., 2024). DT can be utilised not only to support the future measurement of value creation, but also to promote organisational innovation and facilitate the overall value-creation process (Urbinati et al., 2022).

2.3. Key Value-Creation Indicators in Supplier–Buyer Relationships

Theories about enterprise relationships with business partners highlight how value creation is linked to specific indicators. It is important to identify stakeholder needs, determine relevant indicators, and adapt value delivery based on them.

Indicators are measurable variables that reflect organisational performance and support decision-making. Their primary purpose is to enable comparison over time or across contexts (Hales et al., 2010). In the context of B2B value creation, indicators can be both quantitative and qualitative and are often linked to performance, strategy, and stakeholder satisfaction (Kumar et al., 2023). The international standard EN 12973:2020 Value Management defines an indicator as an attribute whose change significantly influences the value of the assessed entity. According to this standard, organisations should define and monitor indicators from both functional and value-based perspectives, ensuring alignment with broader value management objectives (British Standards Institution, 2020). Recent studies also emphasise the role of performance indicators in fostering supplier–buyer collaboration, particularly when sustainability and innovation are included as core dimensions (T. Wang et al., 2017).

The literature identifies many indicators that support value creation, such as operational efficiency, innovation, and relationship quality (Lapierre, 2000). Suppliers value reliable transactions like timely payments and clear terms, while buyers focus more on service improvements and strategic cooperation (Baxter & Matear, 2004). A study by Golicic and Mentzer (2005) found that companies investing in strong buyer–supplier relationships experience improved financial and operational performance.

Research on Central and Eastern European (CEE) markets suggests that regional enterprises emphasise cost efficiency and flexibility in supplier relationships. However, as supply chains globalise, CEE enterprises are increasingly incorporating relationship-driven strategies, aligning with global trends in supplier relationship management (Monczka et al., 2015).

The existing literature underscores the complexity of value creation in B2B relationships, highlighting the need for structured assessment methodologies to effectively capture both tangible and intangible elements of value (Lindgreen & Wynstra, 2005; Nenonen & Storbacka, 2010; Galvagno & Dalli, 2014; Ullah et al., 2025). The decision matrix approach introduced in this study builds on prior research and offers practical insights for Slovak enterprises. By incorporating key value indicators and leveraging technology for quantification, this research contributes to both theoretical and practical discussions in supply chain management. Future studies could further explore industry-specific applications and the integration of advanced analytics in value assessment.

3. Materials and Methods

This paper aims to identify individual value-creation indicators and assign importance levels to them based on supplier and buyer perspectives. The collected data were used to develop a decision matrix to measure the value created for both suppliers and buyers. The research focuses on the B2B sector, specifically targeting manufacturing enterprises. This focus was chosen because these enterprises work with both suppliers and buyers, not only final consumers, which was crucial for data collection. Therefore, only enterprises that met these criteria were selected for the survey.

The research examines value creation for suppliers and buyers as the major stakeholders of the enterprise. One component of the research specifically addresses the identification of individual value-creation indicators and their perceived importance for suppliers and buyers. The initial phase of the research was conducted through online semi-structured interviews with 10 representatives of Slovak manufacturing enterprises. These respondents were selected based on their familiarity with value management practices and their roles as decision-makers in supplier and buyer interactions. Each interview lasted approximately 45–60 min and was conducted via Microsoft Teams. The interviews followed a semi-structured format and were guided by a thematic framework focused on the following: (1) the enterprise’s understanding of value creation in B2B contexts, (2) the types of value they believe they deliver to suppliers and buyers, and (3) their perception of which value indicators are most critical in building strong business relationships. The qualitative insights gained during this phase were used to identify and refine the list of value-creation indicators, which formed the basis for the subsequent questionnaire survey in Phase 2. Subsequently, the research was expanded through an online structured questionnaire, created using Google Forms. This questionnaire was distributed to 10,200 enterprises meeting the specified criteria. The sample included small and medium-sized enterprises (SMEs) from various regions of Slovakia to ensure broad geographical representation. Of the 10,200 enterprises contacted, 412 respondents (4.12%) participated in the survey. The low response rate may be due to time or staff constraints, lack of interest, spam filtering, or the questionnaire’s length. Respondents were primarily managers or owners of manufacturing enterprises in Slovakia. After data cleaning and the exclusion of responses from enterprises that did not meet all criteria, responses from 385 participants were used for further analysis.

The questionnaire focused on various aspects of value creation, including value management, its application, the provision of individual value-creation indicators, and the assignment of importance to those indicators. The questions related to the survey were selected and added to Appendix A.

The determination of the appropriate research sample size was conducted using the following mathematical formulas, commonly used in survey sampling methodology (Yamane, 1969; Raosoft, 2004):

$x={Z({\displaystyle \frac{c}{100}})}^2\times r\times (100-r)$

$n={\displaystyle \frac{N\times x}{\left(N-1\right)E^2+x}}$

$E=\sqrt{{\displaystyle \frac{\left(N-n\right)x}{n(N-1)}}}$

where:

n represents the required sample size,

E denotes the margin of permissible error,

N refers to the total population size,

r is the expected proportion of relevant responses,

Z(c/100) represents the critical value corresponding to the selected confidence level.

The appropriate sample size for the survey was determined using the Raosoft Sample Size Calculator, based on the known population size of 81,149 Slovak manufacturing enterprises at the time of the research (Statistical Office of the Slovak Republic, 2024). The parameters included a 95% confidence level and a 5% margin of error, resulting in a minimum recommended sample size of 383. The final number of valid responses included in the analysis was 385.

To ensure a representative sample, the study targeted small and medium-sized manufacturing enterprises using a random sampling technique. This methodological approach enhances the generalisability of the findings to similar enterprises within Slovakia, ensuring a reliable and insightful analysis.

Descriptive statistical methods, including mean values and frequency distributions, were employed to analyse the collected data in alignment with the survey’s objectives. Additionally, graphical and tabular representations were used to enhance data visualisation, thereby facilitating a clearer and more comprehensive interpretation of the findings.

The data collection process via the questionnaire included information outlining the purpose of data collection and its intended use. Respondents were informed that their participation was voluntary and that the questionnaire was anonymous. Particular emphasis was placed on ensuring respondent anonymity to prevent the identification of individuals from the collected data and to safeguard sensitive information. All participating enterprises were legally registered and operated as manufacturing entities in Slovakia. They were classified as small or medium-sized enterprises based on the number of employees and annual turnover. Participation in the study was entirely voluntary. Enterprises that declined to participate or provided inconsistent or incomplete responses were excluded from the final sample.

The online interviews were conducted via Microsoft Teams with managers and owners of manufacturing enterprises familiar with value management, its principles, and the value-creation process. This phase was essential for identifying the value-creation indicators relevant to suppliers and buyers, which were subsequently incorporated into the questionnaire survey. During the interviews, the value-creation indicators for suppliers and buyers were categorised into groups based on the subject area to which they related.

Based on the interviews, the following value-creation indicators for suppliers were identified (see Figure 1):

Based on the interviews, the following value-creation indicators for buyers were identified (see Figure 2):

In this context, the term “value-creation indicator” includes both quantitative metrics and structured organisational practices that stakeholders perceive as meaningful in supplier–buyer relationships. While some indicators are inherently measurable, such as “Regularity of orders” (e.g., monthly, quarterly) or “Volume discounts” (e.g., ≥20% for large orders); others, like “Team-building activities” or “Increasing order quantities” are practice-based but were explicitly operationalised into measurable forms. For instance, team-building was assessed using a binary scale (Yes/No), while order quantities were evaluated based on observed frequency trends or comparative benchmarks. Although the operationalisation of these indicators is inherently subjective and may vary across enterprises, their consistent mention during the qualitative phase and amenability to structured tracking justified their inclusion in the matrix. This approach ensured that all included elements—whether behavioural or quantitative—could be evaluated systematically and contribute meaningfully to value assessment.

The respondents were asked whether they provide specific value-creation indicators to their business partners (suppliers and buyers). In response, they selected the indicators they actively share with these partners. Subsequently, respondents were also asked to evaluate the importance they attribute to each value-creation indicator. Their responses were recorded using a five-point scale, where a score of 1 represented no importance, 2 indicated more unimportant than important, 3 was considered neutral, 4 signified more important than unimportant, and 5 indicated high importance.

The survey faced several challenges, including a relatively low response rate (4.12%). Data quality issues arose due to incomplete or inconsistent responses, as well as the presence of self-reporting bias. Ensuring a representative sample posed an additional challenge, as the distribution of responses across regions and industry segments may not have been uniform. Defining and measuring value-creation indicators also proved complex, given that perceptions of value differ among enterprises. The data collection methodology, which relied on online surveys and interviews, introduced potential risks such as misinterpretation of questions and limited depth in responses. Furthermore, maintaining anonymity and encouraging honest feedback were essential but difficult, as some enterprises may have been reluctant to share sensitive information. Finally, statistical limitations—including the reliance on descriptive statistics and the margin of error inherent in the sample—required careful consideration when generalising the findings. To mitigate these challenges, several measures were implemented. A random selection of participants was used to enhance representativeness, ensuring that responses reflected the broader population of small and medium-sized manufacturing enterprises. Follow-up reminders were sent to increase participation and improve the response rate. Anonymity and confidentiality were strictly maintained to promote honest and accurate responses, reducing the risk of self-reporting bias. Pilot testing of the survey instrument was carried out to improve question clarity and ensure respondents accurately understood the indicators being measured. Additionally, data cleaning procedures were applied to remove incomplete or inconsistent responses, thereby improving the overall quality of the dataset. Finally, descriptive statistical methods, along with visual data presentation tools such as graphs and tables, were employed to enhance clarity and comprehensibility, ensuring that the findings could be effectively analysed and interpreted.

4. Results

4.1. Provision of Value-Creation Indicators for Suppliers

The value-creation indicators for suppliers were defined in Section 3—Materials and Methods. As part of the survey, enterprises were asked to indicate which of these value-creation indicators they actively provide to their suppliers.

The most commonly provided value-creation indicator was timely payment of invoices, reported by 87.33% (337) of respondents. Additionally, 86.49% (333) of respondents stated that they ensure adherence to business terms. A total of 72.99% (281) indicated that they pay their liabilities on time or make lump-sum payments, while 70.13% (270) reported maintaining regular order patterns.

Other frequently provided value-creation indicators, offered by more than 40% of enterprises, include the following: relationships beyond contractual terms, willingness to communicate when resolving issues (69.87%; 269), space for joint problem-solving (52.47%; 202), providing feedback (49.09%; 189), increasing order frequency and order quantities (41.82%; 161), team-building activities with business partners (41.04%; 158), and business meetings (41.04%; 158).

The least commonly provided indicators include regular company newsletters (4.94%; 19), a reward system for compliance with business terms (9.61%; 37), satisfaction surveys (15.06%; 58), and providing information on the company’s solvency (15.32%; 59) (see Figure 3 below).

4.2. Provision of Value-Creation Indicators for Buyers

Value-creation indicators for buyers were defined in Section 3—Materials and Methods. Within the questionnaire, enterprises were asked to indicate which of these value-creation indicators they provide to their buyers.

The most commonly provided value-creation indicator was additional services in the form of maintenance or repairs, reported by 71.17% (274) of respondents. Additionally, 65.45% (252) of respondents stated that they deliver value by reducing delivery time, and 65.19% (251) do so by offering price reductions, volume discounts, and discounts for loyal business partners.

Other value-creation indicators provided by more than 45% of enterprises include the following: information on product quality and updates (64.16%; 247), anniversary and seasonal promotions (56.62%; 218), space for joint problem-solving (56.62%; 218), favourable warranty conditions (48.83%; 188), and reduction in order processing time (47.27%; 182).

The least frequently provided value-creation indicators include team-building activities with business partners (14.03%; 54), regular company newsletters (9.09%; 35), and reward systems for adhering to business terms (8.31%; 32) (see Figure 4 below).

Some of the value-creation indicators for suppliers and buyers have been shortened for display purposes in the charts; their full names are listed in Figure 1 and Figure 2. Additionally, certain indicators were combined for research purposes to streamline the analysis.

4.3. Process of Creating the Value Measurement Matrix

The measurement of value provided to suppliers and buyers is carried out using individual value-creation indicators offered to them, along with the level of importance attributed to these indicators by suppliers and buyers. The subjectivity inherent in this method is mitigated by the large number of evaluating entities (respondents).

The process of creating the value measurement matrix follows these steps (see Figure 5 below):

The first step is the identification of value-creation indicators. These indicators were identified during the interviews and are defined in Section 3—Materials and Methods. The next step involves assigning a level of importance to each indicator. Respondents rated the importance of the value-creation indicators provided to them by their suppliers and buyers. This was measured on a five-point scale, where 1 represented no importance, 2 meant more unimportant than important, 3 was neutral, 4 signified more important than unimportant, and 5 denoted high importance.

Based on the evaluation of 385 respondents, the importance of individual value-creation indicators was assessed separately for buyers and suppliers using the average score.

The decision matrix does not distinguish between different types of indicators (e.g., quantitative vs. behavioural). All identified indicators—whether objectively measurable (e.g., frequency of orders, discount percentages) or behaviour-based (e.g., team-building activities, joint problem-solving)—are assessed using the same structure. The matrix reflects the perceived importance of each indicator, as evaluated by the stakeholders. This approach ensures the inclusion of even context-specific or subjective practices, highlighting the real-world relevance of both tangible and relational value-creation elements.

The value measurement matrix was developed in two stages. First, value-creation indicators were identified through qualitative interviews and structured into two parallel lists—one for suppliers and one for buyers. Second, these indicators were evaluated by 385 enterprises using a standardised online questionnaire. Respondents rated each indicator on a five-point Likert scale, from 1 (“no importance”) to 5 (“high importance”). These scores were averaged to produce an importance weight for each indicator, reflecting a consensus on which are most critical to value in supplier–buyer relationships.

These weights are based on stakeholder perceptions rather than statistical optimisation or objective performance data. This reflects the subjective and relational nature of value creation in B2B settings, where soft factors, such as trust-building activities or responsiveness, can be decisive. Some indicators in the matrix are quantifiable (e.g., order frequency, volume discounts), while others reflect structured practices (e.g., regular feedback, joint process improvement). Despite their varied forms, all were treated as evaluable and included in a unified scoring system. This enables practical comparison in strategic decision-making, integrating both operational and relational dimensions of value as perceived by enterprises.

4.4. Significance of Value-Creation Indicators Provided to Suppliers and Buyers and Their Average Score

Respondents assigned levels of importance to individual indicators. Based on the results, an average importance score was calculated for each value-creation indicator. In Figure 6, the value-creation indicators for suppliers are ranked from most to least important, with each indicator presented alongside its average score.

As shown in the figure, the most important value-creation indicators for suppliers include adherence to business terms (average score: 4.56), timely payment of invoices (4.52), on-time settlement of liabilities and shortening of payment deadlines (4.27), and relationships beyond contractual terms (4.11). These indicators were assigned high importance by the respondents.

Conversely, the least important indicators include regular meetings and reward systems for complying with business terms (both with a score of 2.94), customer satisfaction surveys (2.93), and regular company newsletters (2.59). Respondents either expressed neutrality or viewed these as less important.

Similarly, the value-creation indicators for buyers were evaluated, and their average scores were calculated based on the levels of importance assigned by respondents. In Figure 7, the indicators are ranked from most to least important, with their corresponding average scores.

As shown in Figure 7, no indicator achieved an average score above 4, indicating that none were considered highly important by the respondents. The most important indicators (rated as more important than unimportant) include additional services (e.g., maintenance and repairs) with a score of 4.02, information about product quality and changes with 4.01, shortened delivery time with 3.93, reduced order processing time with 3.81, and favourable warranty conditions with 3.79.

In contrast, the least important indicators were regular meetings (2.99), customer satisfaction surveys (2.98), reward systems for adhering to business terms (2.91), team-building activities (2.70), and regular company newsletters (2.58).

4.5. Importance Weights, Matrix Creation, and Value Calculation

The next step involved creating importance weights based on predefined intervals. Each value-creation indicator was assigned a weight according to the interval in which its average importance score falls. To ensure consistent interpretation across the full scale, all intervals in the histogram were adjusted to a uniform width of 0.25, covering the entire 0–5 range, regardless of the frequency of values in lower segments.

Once the weights were defined, they were assigned to each indicator. The weight corresponded to the interval where the indicator’s average importance score fell (see Figure 8). These weights for suppliers and buyers are shown in Figure 6 and Figure 7.

The final steps involved constructing the matrix and calculating the value provided. Separate matrices were created for buyers and suppliers (Figure 9 and Figure 10). The calculation identifies the value-creation indicators that an enterprise provides. If all listed indicators are provided, the enterprise delivers 100% of the value. The percentage is calculated by dividing the sum of the importance-weighted indicators by the total sum of all importance weights.

Both matrices were developed in Microsoft Excel and are designed to calculate the value delivered automatically. The enterprise simply fills in a column by entering 1 (indicator provided) or 0 (indicator not provided). The matrix then calculates the percentage of value delivered.

The indicators are listed from most to least important. Enterprises can view the associated importance weights and use this to identify which high-value indicators they are not currently providing, helping to prioritise improvements in their value-creation strategy.

To support practical use, a Google Sheets version of the matrix was created. It is accessible via the QR code in Figure 11. The sheet includes two tabs—one for suppliers and one for buyers. Enterprises enter 1 if they provide a specific indicator and 0 if not. A 100% score indicates all indicators are provided. Lower scores highlight areas for improvement, particularly those deemed important by stakeholders.

5. Discussion

5.1. Implications for Theory

The findings of the survey, which measured the value created for suppliers and buyers using a decision matrix, provide key insights into how Slovak manufacturing enterprises perceive and deliver value to their main stakeholders. The results confirm that enterprises prioritise specific value-creation indicators, aligning with global trends reported in the State of Flux SRM research, which emphasises the importance of long-term, mutually beneficial partnerships (State of Flux, 2023).

Suppliers considered adherence to business terms (average score: 4.56) and timely payment of invoices (4.52) as the most critical indicators. This finding supports the 2024 State of Flux SRM report, which highlights financial reliability as a key contributor to resilient supplier relationships. According to the report, 46% of participants stated that their supplier management programmes delivered financial benefits exceeding 4% per annum, demonstrating the tangible impact of financial stability on supplier partnerships (State of Flux, 2024).

On the other hand, the least important indicators for suppliers were regular company newsletters (2.59) and customer satisfaction surveys (2.93). This supports the 2022 State of Flux report, in which communication tools were not seen as major drivers of supplier satisfaction (State of Flux, 2022). However, our earlier research suggests that communication still plays an essential theoretical role. In fact, 86% of enterprises reported using mutual communication to support their value-creation processes, underlining the ongoing importance of relational factors—even if they are not always prioritised in numerical evaluations (Kusnirova et al., 2024).

For buyers, the most important indicators were additional services (e.g., maintenance and repairs, score: 4.02) and information about product quality and changes (4.01). This aligns with the 2024 State of Flux concept of Return on Relationships (ROR), which emphasises innovation and operational efficiency as central to stakeholder value (State of Flux, 2024). These findings confirm theoretical insights regarding the value of operational improvements and service enhancements in B2B settings (Grönroos & Helle, 2010; Johnston et al., 2025).

5.2. Implications for Managers and Policymakers

The results carry several practical implications. Suppliers clearly prioritise financially reliable partners, and buyers seek information and services that directly improve operational performance. These insights help managers better align their relationship strategies with stakeholder expectations. In particular, the prioritisation of transactional indicators reflects a strong emphasis on operational execution.

Interestingly, none of the value-creation indicators for buyers received an average score above 4, indicating a generally moderate level of perceived importance. This contrasts with the 2022 SRM report, in which organisations placed more emphasis on strategic alignment and joint value creation (State of Flux, 2022). The discrepancy suggests that Slovak manufacturing enterprises may currently focus more on operational reliability than on long-term strategic partnerships.

Our earlier research supports this aforementioned interpretation. Only 30.91% of respondents reported complete satisfaction with their buyer relationships, while 69.09% acknowledged there was room for improvement (Kusnirova et al., 2024). Managers should consider enhancing relational elements such as co-innovation, trust-building, and transparent communication, which have been shown to strengthen partnership quality (Kusnirova et al., 2023).

The decision matrix introduced in this study offers a practical tool for enterprise use. It allows companies to assess how much value they provide based on what their business partners consider important. By identifying gaps—i.e., high-value indicators that are not currently provided—managers can improve strategic resource allocation.

The findings also point to a broader need for policy support. Only 38% of enterprises are familiar with value management, and just 26% actively apply it in stakeholder relationships (Kusnirova et al., 2024). This suggests an opportunity for public institutions or industry associations to offer targeted education or support programmes to improve awareness and implementation of value management strategies.

5.3. Limitations of the Study and Future Research Directions

A key challenge noted in this research is the subjectivity involved in assigning importance weights to value-creation indicators. Although this was partially mitigated by the relatively large sample size of 385 respondents, which provides a statistically robust basis for analysis, the results are ultimately based on self-reported perceptions. The 2024 State of Flux SRM report similarly acknowledged the difficulty in fully quantifying the broader returns from supplier relationships (State of Flux, 2024).

The 2023 State of Flux report also highlights a common gap between reported benefits and measurable outcomes. For example, while 38% of enterprises reported cost reduction, only 42% were able to quantify these benefits. Similarly, 65% cited collaborative problem-solving as valuable, but just 11% could link it to measurable financial outcomes (State of Flux, 2023). These results confirm that value in supplier–buyer relationships should not be assessed purely through financial metrics.

To support a broader understanding of value creation, the decision matrix developed in this study enables enterprises to calculate the percentage of value delivered based on clearly defined indicators and stakeholder input. This offers a more nuanced and comprehensive overview of the value exchanged.

The findings suggest that Slovak enterprises, while currently focused on transactional performance, could gain additional benefits by emphasising strategic relationship management. According to the 2024 SRM report, organisations recognised as buyers of choice benefit from advantages such as priority access to supply, reduced risk exposure, and co-created innovation (State of Flux, 2024). However, as noted, only a minority of Slovak enterprises are actively applying value management principles (Kusnirova et al., 2024).

Aligned with our earlier work, this study reinforces the link between specific value-creation indicators and the overall quality of supplier–buyer relationships (Kusnirova et al., 2023). The matrix offers a user-friendly tool for self-assessment and continuous improvement, helping firms transition from transactional to strategic partnerships in line with global SRM practices.

6. Conclusions

This survey provides valuable insights into the value-creation process for suppliers and buyers within Slovak manufacturing enterprises. Using a decision matrix approach, it offers a structured method for identifying key value-creation indicators, assigning levels of importance to these indicators, and quantifying the value delivered to stakeholders. The findings underscore the critical importance of transactional elements—such as adherence to business terms and timely invoice payment—for suppliers, while buyers prioritise additional services and information about product quality and updates.

Conclusion for Practice: The decision matrix effectively measures value and offers actionable insights, revealing that many enterprises continue to focus on operational reliability over long-term strategic relationships. It also serves as a practical tool for evaluating and improving partnerships with buyers and suppliers. By identifying the indicators most valued by stakeholders, enterprises can allocate resources more efficiently and enhance relationship management. Investing in deeper partnerships and encouraging collaborative innovation may increase enterprise resilience, reduce risk, and provide a competitive advantage in today’s interconnected business environment. Furthermore, using Microsoft Excel for automated value calculation makes the approach user-friendly and suitable for continuous assessment.

Conclusion for Research: From a research perspective, this study contributes to a broader understanding of value creation in B2B relationships. The decision matrix introduces a novel framework for quantifying value beyond purely financial metrics, capturing both transactional and relational dimensions of stakeholder engagement.

Future research could expand on this study by testing or comparing alternative methodological frameworks that deliver more dynamic, data-driven, or stakeholder-specific insights. For example, fuzzy logic-based models could better handle ambiguity and subjectivity in the evaluation of value indicators, particularly when linguistic labels (e.g., “high importance”, “moderate importance”) are more suitable than numerical scores. Additionally, techniques such as cluster analysis could help segment enterprises or stakeholders based on value priorities, uncovering patterns not visible through aggregate data. Simulation modelling or agent-based approaches could be employed to explore how changes in supplier–buyer interactions affect long-term value dynamics. These methods may provide deeper insights into value exchange mechanisms and offer more flexible tools for developing enterprise-level strategies, especially in fast-changing or uncertain environments.

Author Contributions

Conceptualization, D.K. and M.D.; methodology, D.K. and M.D.; data collection, D.K. and O.B.; validation, D.K. and O.B.; writing—original draft preparation, D.K.; writing—review and editing, D.K., O.B. and M.D.; visualization, D.K.; supervision, D.K.; project administration, D.K. and M.D. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The study involved anonymous questionnaires completed by representatives of small and medium-sized enterprises (SMEs). It was entirely non-interventional and did not include any collection of sensitive or personally identifiable data. All data were handled securely and in full compliance with GDPR requirements, and are archived at the Faculty of Management Science and Informatics, University of Žilina. In Slovakia, Act No. 131/2002 Coll. on Higher Education Institutions delegates ethical oversight of research to public universities.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Dataset available on request from the authors.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:

SRM	Supplier Relationship Management
B2B	Business to Business
ROR	Return on Relationships
MCDM	Multi-criteria decision-making
AHP	Analytical Hierarchy Process
TOPSIS	Technique for Order Preference by Similarity to Ideal Solution
DMM	Decision Matrix Method
DT	Digital Transformation

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures

Figure 1 Value-creation indicators for suppliers.

Figure 2 Value-creation indicators for buyers.

Figure 3 Provision of value-creation indicators for suppliers.

Figure 4 Provision of value-creation indicators for buyers.

Figure 5 Process of creating the value measurement matrix.

Figure 6 Average score and importance weights of value-creation indicators for suppliers.

Figure 7 Average score and importance weights of value-creation indicators for buyers.

Figure 8 Importance weights.

Figure 9 Matrix—value created for suppliers.

Figure 10 Matrix—value created for buyers.

Figure 11 QR code—Google Sheets for measuring value created for suppliers and buyers.

Appendix A

For the purposes of this paper, the questions related to the survey were selected and added to Appendix A.

Question	Answer
What value (indicators) does your company provide to its suppliers? Please select from the following indicators. (Mark all applicable options).	List of the value-creation indicators for suppliers (see Figure 1).
How important are the individual indicators (related to the previous question) to your company? Please rate their importance on a scale from 1—not important at all to 5—very important.	1—No importance,2—More unimportant than important,3—Neutral,4—More important than unimportant,5—High importance.
What value (indicators) does your company provide to its buyers? Please select from the following indicators. (Mark all applicable options).	List of the value-creation indicators for buyers (see Figure 2).
How important are the individual indicators (related to the previous question) to your company? Please rate their importance on a scale from 1—not important at all to 5—very important.	1—No importance,2—More unimportant than important,3—Neutral,4—More important than unimportant,5—High importance.

References

Anderson, J. C.; Narus, J. A.; Narayandas, D. Business market management: Understanding, creating, and delivering value; 3rd ed. Person: 2008.

Aruldoss, M.; Lakshmi, T. M.; Venkatesan, V. P. A survey on multi criteria decision making methods and its applications. American Journal of Information Systems; 2013; 1, 1 pp. 31-43.

Baxter, R.; Matear, S. Measuring intangible value in business-to-business buyer-seller relationships: An intellectual capital perspective. Industrial Marketing Management; 2004; 33, 6 pp. 491-500. [DOI: https://dx.doi.org/10.1016/j.indmarman.2004.01.008]

Bouncken, R.; Kumar, A.; Connell, J.; Bhattacharyya, A.; He, K. Coopetition for corporate responsibility and sustainability: Does it influence firm performance?. International Journal of Entrepreneurial Behavior & Research; 2024; 30, 1 pp. 128-154.

British Standards Institution. Value management (BS EN 12973:2020); BSI Standards Publication: 2020.

Christopher, M. Logistics and supply chain management; 6th ed. Pearson: 2016.

Ciampi, F.; Demi, S.; Magrini, A.; Marzi, G.; Papa, A. Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation. Journal of Business Research; 2021; 123, pp. 1-13. [DOI: https://dx.doi.org/10.1016/j.jbusres.2020.09.023]

De Boer, L.; Labro, E.; Morlacchi, P. A review of methods supporting supplier selection. European Journal of Purchasing and Supply Management; 2001; 7, 2 pp. 47-89. [DOI: https://dx.doi.org/10.1016/S0969-7012(00)00028-9]

Eggert, A.; Ulaga, W.; Frow, P.; Payne, A. Conceptualizing and communicating value in business markets: From value in exhange to value in use. Industrial Marketing Management; 2018; 69, 2018 pp. 80-90. [DOI: https://dx.doi.org/10.1016/j.indmarman.2018.01.018]

Freeman, R. E.; Dmytriyev, S. D.; Phillips, R. A. Stakeholder theory and the resource-based view of the firm. Journal of Management; 2021; 47, 5 pp. 1757-1770. [DOI: https://dx.doi.org/10.1177/0149206321993576]

Freudenreich, B.; Ludeke-Freund, F.; Schaltegger, S. A stakeholder theory perspective on business models: Value creation for sustainability. Journal of Business Ethics; 2020; 166, 1 pp. 3-18. [DOI: https://dx.doi.org/10.1007/s10551-019-04112-z]

Galvagno, M.; Dalli, D. Theory of value co-creation: A systematic literature review. Managing Service Quality: An International Journal; 2014; 24, 6 pp. 643-683. [DOI: https://dx.doi.org/10.1108/MSQ-09-2013-0187]

Golicic, S. L.; Mentzer, J. T. Exploring the drivers of interorganizational relationship magnitude. Journal of Business Logistics; 2005; 26, 2 pp. 47-71. [DOI: https://dx.doi.org/10.1002/j.2158-1592.2005.tb00205.x]

Gouveia, S.; De La Iglesia, D. H.; Abrantes, J. L.; Rivero, A. J. L. Transforming strategy and value creation through digitalization?. Administrative Sciences; 2024; 14, 11 307. [DOI: https://dx.doi.org/10.3390/admsci14110307]

Grönroos, C. Value co-creation in service logic: A critical analysis. Marketing Theory; 2011; 11, 3 pp. 279-301. [DOI: https://dx.doi.org/10.1177/1470593111408177]

Grönroos, C.; Helle, P. Adopting a service logic in manufacturing: Conceptual foundation and metrics for mutual value creation. Journal of Service Management; 2010; 21, 5 pp. 564-590. [DOI: https://dx.doi.org/10.1108/09564231011079057]

Hales, D.; Peersman, G.; Rugg, D.; Kiwango, D. UNAIDS, an introduction to indicators. UNAIDS monitoring and evaluation fundamentals; 2010; Available online: https://www.unaids.org/sites/default/files/sub_landing/files/8_2-Intro-to-IndicatorsFMEF.pdf (accessed on 10 March 2025).

Harrison, J. S.; Wicks, A. Stakeholder theory, value, and firm performance. Business Ethics Quarterly; 2013; 23, 1 pp. 97-125. [DOI: https://dx.doi.org/10.5840/beq20132314]

Hayslip, T. B.; Gallarz, M. G.; Andreu, L. Service-dominant logic and value in tourism management: A qualitative study within Spanish hotels managers. Journal of Business Theory and Practice; 2013; 1, 2 pp. 303-328. [DOI: https://dx.doi.org/10.22158/jbtp.v1n2p303]

Ho, W.; Xu, X.; Dey, P. K. Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research; 2010; 202, 1 pp. 16-24. [DOI: https://dx.doi.org/10.1016/j.ejor.2009.05.009]

Jaaskelainen, A. The relational outcomes of performance management in buyer-supplier relationships. International Journal of Production Economics; 2021; 232, pp. 1-14. [DOI: https://dx.doi.org/10.1016/j.ijpe.2020.107933]

Johnston, M. W.; Marshall, G. W.; Ogilvie, J. L. Contemporary selling—Building relationships, creating value; 7th ed. Routledge: 2025.

Kmetík, M.; Huška, R.; Melichar, V. Using the decision matrix method for transportation of oil products by inland waterway transport. Perner’s Contacts; 2019; 14, 3 pp. 41-48.

Korsgaard, M. A.; Kautz, J.; Bliese, B.; Samson, K.; Kostyszyn, P. Conceptualising time as a level of analysis: New directions in the analysis of trust dynamics. Journal of Trust Research; 2018; 8, 2 pp. 142-165. [DOI: https://dx.doi.org/10.1080/21515581.2018.1516557]

Krause, D. R.; Ellram, L. M. Success factors in supplier development. International Journal of Physical Distribution and Logistics Management; 1997; 27, 1 pp. 39-52. [DOI: https://dx.doi.org/10.1108/09600039710162277]

Kucharcikova, A.; Miciak, M.; Tokarcikova, E.; Staffenova, N. The investments in human capital within the human capital management and the impact on the Enterprise’s performance. Sustainability; 2023; 15, 6 5015. [DOI: https://dx.doi.org/10.3390/su15065015]

Kumar, A.; Shrivastav, S. K.; Shrivastava, A. K.; Panigrahi, R. R.; Mardani, A.; Cavallaro, F. Sustainable supply chain management, performance measurement, and management: A review. Sustainability; 2023; 15, 6 5290. [DOI: https://dx.doi.org/10.3390/su15065290]

Kusnirova, D.; Bubeliny, O.; Durisova, M. Value management: Enterprises’ interest in stakeholders and its impact on creating sustainable relationships with suppliers and buyers. Sustainability; 2024; 16, 16 7148. [DOI: https://dx.doi.org/10.3390/su16167148]

Kusnirova, D.; Durisova, M.; Malichova, E. Indicators of value creation and their perception by suppliers in Slovakia. Administrative Sciences; 2023; 13, 8 174. [DOI: https://dx.doi.org/10.3390/admsci13080174]

Lapierre, J. Customer-perceived value in industrial contexts. Journal of Business & Industrial Marketing; 2000; 15, 2/3 pp. 122-145. [DOI: https://dx.doi.org/10.1108/08858620010316831]

Leso, B. H.; Cortimiglia, M. N.; Ghezzi, A. The contribution of organizational culture, structure, and leadership factors in the digital transformation of SMEs: A mixed-methods approach. Cognition, Technology & Work; 2023; 25, pp. 151-179.

Lindgreen, A.; Wynstra, F. Value in business markets: What do we know? Where are we going?. Industrial Marketing Management; 2005; 34, 7 pp. 732-748. [DOI: https://dx.doi.org/10.1016/j.indmarman.2005.01.001]

Lopes, A. P.; Rodriguez-Lopez, N. A decision support tool for supplier evaluation and selection. Sustainability; 2021; 13, 22 12387. [DOI: https://dx.doi.org/10.3390/su132212387]

Máca, J.; Leitner, B. Aplikácia metód viacriteriálneho rozhodovania v krízovom riadení; FŠI ŽU: 2002.

Monczka, R.; Handfield, R.; Giunipero, L.; Patterson, J. Purchasing and supply chain management; 6th ed. Cengage Learning: 2015.

Nenonen, S.; Storbacka, K. Business model design: Conceptualizing networked value co-creation. International Journal of Quality and Service Sciences; 2010; 2, 1 pp. 43-59. [DOI: https://dx.doi.org/10.1108/17566691011026595]

Nguyen, T. L.; Nguyen, V. K.; Nguyen, T. C. Buyer-supplier contract length and the innovation of supplier firms. Journal of Open Innovation: Technology, Market, and Complexity; 2020; 6, 3 52. [DOI: https://dx.doi.org/10.3390/joitmc6030052]

Raosoft,. Sample size calculator; 2004; Available online: http://www.raosoft.com/samplesize.html (accessed on 10 March 2025).

Schiele, H.; Calcvi, R.; Gibbert, M. Customer attactiveness, supplier satisfaction and preferred customer status: Introduction, definitions and an overarching framework. Industrial Marketing Management; 2012; 41, 8 pp. 1178-1185. [DOI: https://dx.doi.org/10.1016/j.indmarman.2012.10.002]

State of Flux Ltd. Global SRM research report—Building resilience; 2022; Available online: https://ebooks.stateofflux.co.uk/view/660078291/?hsCtaTracking=7a30209f-6c78-44c2-baf0-b45aced3666b%7C6d9b2987-1eec-470b-9fb2-22a046a75d79 (accessed on 10 March 2025).

State of Flux Ltd. Global SRM research report—Extended enterprise; 2023; Available online: https://ebooks.stateofflux.co.uk/view/584904776/?hsCtaTracking=e5ecb108-f43c-4a3b-a8e2-739e601290d4%7C76d3144e-67be-4674-bb81-19e6ad4d8cc9 (accessed on 10 March 2025).

State of Flux Ltd. Global SRM research report—Return on relationships; 2024; Available online: https://ebooks.stateofflux.co.uk/view/404695839/ (accessed on 10 March 2025).

Statistical Office of the Slovak Republic. Business demography: Number of enterprises by economic activity; 2024; Available online: https://datacube.statistics.sk (accessed on 10 March 2025).

Storbacka, K.; Frow, P.; Nenonen, S.; Payne, A. Designing business models for value co-creation. Review of Marketing Research; 2012; 9, pp. 51-78. [DOI: https://dx.doi.org/10.1108/S1548-6435(2012)0000009007]

Tescari, F. C.; Brito, L. A. L. Value creation and capture In Buyer-Supplier relationships: A new perspective. Revista de Administracao de Empresas; 2016; 56, 5 pp. 474-488. [DOI: https://dx.doi.org/10.1590/s0034-759020160503]

Ullah, F.; Lei, S.; Newton, J. K.; Lund, D. W. TCM-AVC model: A systematic literature review on value co-creation in B2B and research agenda. Sustainability; 2025; 14, 5 2021. [DOI: https://dx.doi.org/10.3390/su17052021]

Urbinati, A.; Manelli, L.; Frattini, F.; Bogers, M. L. A. M. The digital transformation of the innovation process: Orchestration mechanisms and future research directions. Innovation; 2022; 24, pp. 65-85. [DOI: https://dx.doi.org/10.1080/14479338.2021.1963736]

Vargo, S. L.; Lusch, R. F.; Akaka, M. A. On value and value co-creation: A service systems and service logic perspective. European Management Journal; 2008; 26, 3 pp. 145-152. [DOI: https://dx.doi.org/10.1016/j.emj.2008.04.003]

Vos, F. G.; Schiele, H.; Huttinger, L. Supplier satisfaction: Explanation and out-of sample prediction. Journal of Business Research; 2016; 69, 10 pp. 4613-4623. [DOI: https://dx.doi.org/10.1016/j.jbusres.2016.04.013]

Walter, A.; Ritter, T.; Gemunden, H. G. Value creation in buyer-seller relationships: Theoretical considerations and empirical results from a Supplier’s perspective. Industrial Marketing Management; 2001; 30, 4 pp. 365-377. [DOI: https://dx.doi.org/10.1016/S0019-8501(01)00156-0]

Wang, C.; Tsai, H.; Ho, T.; Nguyen, V.; Huang, Y. Multi-criteria decision making (MCDM) model for supplier evaluation and selection for oil production projects in Vietnam. Processes; 2020; 8, 2 134. [DOI: https://dx.doi.org/10.3390/pr8020134]

Wang, T.; Zhang, Q.; Chong, H.; Wang, X. Integrated supplier selection framework in a resilient construction supply chain: An approach via analytic hierarchy process (AHP) and grey relational analysis (GRA). Sustainability; 2017; 9, 2 289. [DOI: https://dx.doi.org/10.3390/su9020289]

Yamane, T. Statistics an introductory analysis; 2nd ed. Harper & Row: 1969.

Yang, M.; Leposky, T. An entrepreneurial framework for value co-creation in servitization. Industrial Marketing Management; 2022; 107, pp. 484-497. [DOI: https://dx.doi.org/10.1016/j.indmarman.2022.11.002]

Zeiller, M.; Edlinger, K. A decision matrix for choosing the proper visualization technique in knowledge visualization. Tenth IASTED International Conference Computer Graphics and Imaging; Innsbruck, Austria, February 13–15; 2008.

Zeng, X. Supplier relationship assessment. Learning and Education; 2020; 9, 4 pp. 226-229. [DOI: https://dx.doi.org/10.18282/l-e.v9i4.1739]