It is postulated by stakeholder theory that an important component of value creation in businesses, which augments their probabilities of being efficacious, is their engagement and development of strong relations with a wide range of stakeholders (Harrison, Bosse, & Phillips, 2010 [21] ; Campanella et al., 2016 [22] ; Pollack, Barr, & Hanson, 2017 [23] ; Sefiani et al., 2018 [24] ). An emergent number of scholars are studying the involvement of stakeholders and the role they play in the strategic management of an organization (De Gooyert et al., 2017 [1] ; Miles, 2017 [2] ; Sefiani et al., 2018 [24] ). Nevertheless, to the best of the researcher’s knowledge, none of these studies has considered the driving factors for effective stakeholder management and SME performance, with regard to the relative ranks of their importance. Against this background, the resolution of this study was to determine the relative degree of significance of the driving factors for effective stakeholder management and SME performance. The relevant driving factors were identified from a far-reaching and conscientious literature review. The decision framework established and used in this study emanated from a view of stakeholder theory through the macro, meso and micro dimensions, and the best-worst method (BWM) was used to scrutinize and rank the recognized driving factors for effective stakeholder management and performance of SMEs according to their weighted averages. This quirky research sought to develop a theoretical framework to study the driving factors for effective stakeholder management and performance of SMEs, with regard to the relative importance of these driving factors. This study lays emphasis on the relative status of relevant driving factors derived from literature, but is not really focused on the desk research and detection of another fundamental driving factor for effective stakeholder management. The known driving factors for effective stakeholder management and SME performance, from existing literature, were debated through the lens of stakeholder theory with respect to macro, meso and micro dimensions.

The decision framework developed in this research, underpinned by stakeholder theory, was derived from three dimensions, namely macro (global, national, and international issues), meso (industry, market, and technology), and micro (individual actors) contexts, as adopted by Belousova, Groen and Ouendag (2020) [17] . This innovative framework was used to explore the weights and rankings of the driving factors that significantly impact effective stakeholder management and SME performance. The new model categorized the driving factors for effective stakeholder management by entrepreneurs and SMEs into macro, meso and micro dimensions, as depicted in Table 1. Within each of these dimensions, there were driving factors recognized by an amalgamation of literature from previous studies and opinions of stakeholder management and entrepreneurship experts.

The BWM is a multi-criteria decision-making model which evaluates the weights of criteria by using two vectors of pair wise comparisons between the most important and the least important criteria (Wang et al., 2019) [20] . The steps below are involved in evaluating the weights of criteria using the BWM (Rezaei, 2016) [19] .

Step 1: Finalization of decision criteria.

A set of decision criteria are identified and extracted from an intensive search of literature, and experts’ opinions and recorded as {C1, C2, ..., Cn} for n main criteria. In this study, the decision criteria are the driving factors for effective stakeholder management and performance of SMEs.

Step 2: The best (most important) and worst (least important) criteria are selected.

At this juncture, the expert selects the most important and least important criteria from the pool of identified decision criteria in Step 1 based on his/her opinion.

Step 3: A matrix is developed by determining the pair wise comparison between the most important criterion and the other decision criteria. The objective of this step is to determine the preference of the most important criterion to the other decision criteria by using a linguistic scale for the BWM having scores from 1 to 9. The linguistic scale is shown in Table 2. The outcome of the pair wise comparison of the best criterion and other decision criteria is expressed by a “best-to-others” vector as follows:

DB = (dB1, dB2, ..., dBn)

where dBj represents the preference of the most important criterion B over a criterion j amongst the decision criteria, and dBB = 1

Step 4: The “others-to-worst” matrix is developed by conducting a pair-wise comparison of the other decision criteria against the least important criterion using the linguistic scale for BWM shown in Table 2. The outcome of comparison of the other decision criteria to the worst criterion is expressed as follows:

DW = (dW1, dW2, ..., dWn)^q

where dWj represents the preference of the criterion j amongst the decision criteria in Step 1 above the least important criterion W, and dWW = 1.

Step 5: Computing the optimal weights (p1*, p2*, ..., pn*).

Weights of criteria are determined such that the maximum absolute differences for all criterion j are minimised over the following set {|pB − dBjpj|, |pj − djW pW|}.

Source: Authors’ own construct.

A minimax model can be formulated as:

min max j{|pB − dBjwj|, |pj − djWwW|}

Subject to:

∑_jpj = 1 (1)

pj ≥ 0, for all criterion j

Model (1) can be solved by converting it into the following linear programming problem model:

Min R^L

Subject to:

|pB − dpj| ≤ R^L, for all criterion j

|pj − dpW| ≤ R^L, for all criterion j

∑ j p j = 1

pj ≥ 0, for all criterion j (2)

Solving the linear model (2), will result in optimal weights (p1*, p2*, ..., pn*) and optimal value R^L. Consistency (R^L) of comparisons also needs to be estimated. A value nearer to zero is more desired for consistency (Rezaei, 2016 [19] ; Wang et al., 2019 [20] ).

To conduct this survey, questionnaires were designed and used to gather data from contributors with a minimum of five years of professional management and decision-making experience in the SME and entrepreneurial sector of Ghana. This was done to maintain the accuracy of data gathered since the professionals were reckoned to be reasonably knowledgeable to efficiently complete the appraisal. The experts were purposefully selected from the fields of academia and small- and medium-scale enterprises (SMEs) at various stages of maturity. For the purpose of this survey SMEs were ranked from grade I to IV, where I denotes fresh startups with up to ten employees and IV denotes fully fledged SMEs with over a hundred employees, in that order, respectively The contributors were assured of the concealment of their accounts in order to allow for a working model-building and in-depth observation (Nilashi et al., 2016) [59] . Also, the contributors were selected mid-level and above grade managers, therefore their answers adequately characterized the sector under consideration (Fu et al., 2006) [60] .

Some measures were taken to increase the rate of response and decrease response bias amongst the experts from the selected SMEs during the conduct of the survey. Initially, a pilot study was conducted by distributing the google form questionnaires designed for this inquest to three researchers through emails and interviewing three participants face-to-face to scrutinize responses. The three researchers that participated in the pilot study were two males and a female who hold PhD degrees and have at least five years of research experience in stakeholder management, entrepreneurship, economics and public finance. Also, the specialists who participated in the pilot study have managerial experience of at least five years in the Ghanaian SME sector. Grounded on the responses from the pilot study, the survey questionnaires were upgraded and emailed to twenty-five respondents. Five respondents each were chosen to represent the five different roles of the participants as presented in Table 2. A track on the experts was orchestrated through telephone dialogues and individual follow-up visits (Yang et al. 2018) [61] . Eventually, twenty-one completed questionnaires were retrieved from the twenty-five that were emailed to the participants, a response rate of 84%. This response rate is considered suitable for proficient analysis and to produce consistent findings, according to the BWM used in this study, which does not need a big sample size to deliver precise and consistent results (Wang et al., 2019) [20] .

On the completion of the selection of DFs for effective stakeholder management and performance of SMEs, the weights of the DFs were calculated using the BWM. For this study, twenty-one professionals completed the identification of the best and worst criteria for the main dimensions as well as subcategory criteria DFs. Successive to obtaining the best and worst criteria, all the partakers were requested to give preference ratings of the best criteria to other criteria and other criteria to worst criteria for the main dimension’s criteria DFs as well as subcategory criteria DFs. Table 3 exudes the preference ratings of Expert 1, the first expert, for both the main category criteria DFs, and subcategory criteria DFs.

Source: Authors’ own construct.

A similar process of the BWM survey, as designated in the paragraph above, was finalized by all the partakers in this study to evaluate the performance ratings of the main category and subcategory DFs for effective stakeholder management and performance of SMEs. The entire weights of the DFs for both the main category and subcategory were acquired using Equation (1). All the accumulated weights were calculated by applying the data obtained from the twenty-one contributors to this study to Equation (2) and approximating the mean using the simple average technique. The whole results of the assessment process, facilitated by the BWM, are shown in Table 3. The grade of prominence of a DF is revealed by its ranked position in the table. The global ranks of the identified DFs, as illustrated in Table 3, were computed by multiplying the preference weights of the respective DF’s dimension with the specific weight of the DF. The positions of both the main category dimensions and sub category DFs are deliberated in detail in the next section of this report.

Table 3 encapsulates the results of the calculation of the optimal weights, enabled by the BWM-Solver. From the table, it is can be observed that the meso dimension emanated as the most important dimension for effective stakeholder management and performance of SMEs. It is also observable from the table that the macro and micro dimensions follow respectively in order of importance. It can be deduced from the results that the driving factors for effective stakeholder management and performance of SMEs that are akin to the meso dimensional context are predominantly important and should be sufficiently considered to enhance effective stakeholder management and performance of SMEs. The next in terms of prominence, with regards to the dimensions for effective stakeholder management and performance of SMEs, is the macro dimension. The least ranked dimension, as per the results, is the micro dimension. It is recommended that SME industry managers should be encouraged to operate in line with the driving factors associated with the topmost-ranked context to enhance their prospects for effective stakeholder management and performance.

Table 3 exudes the global ranks of the DFs factors for effective stakeholder management and performance of SMEs. The topmost three DFs under the global ranks, which connote about the top 19% of DFs, belong to the macro and meso dimensional contexts measured in this research. These top DFs are financial slack, stakeholder integration, and social capital. The topmost-ranked DF for effective stakeholder management and performance of SMEs, financial slack, denotes the level of liquid assets available for immediate disposition by an organisation (Kiss, Fernhaber, & McDougall-Covin, 2018) [15] . The results of the study prove that possession of financial slack by SMEs is a critical driving factor for their enhanced performance and effective stakeholder management. The results corroborate studies by researchers such as Ang and Straub (1998) [28] , Voss, Sirdeshmukh, and Voss (2008) [29] and Adomako et al. (2021) [16] , with regards to how he possession of financial slack by SMEs affords them the opportunity to engage in strategic organizational activities that culminate in better performance. The second most important DF in the ordering hierarchy is stakeholder integration. Stakeholder integration means partnerships whereby a firm’s stakeholders such as customers, communities and suppliers inform the firm’s practices to deliver better performance (Amankwah-Amoah, Danso, & Adomako, 2019 [43] ; Desai, 2018 [48] ). It has been suggested by Danso et al. (2019) [47] that the influence of an organisation’s environmental sustainability orientation on its financial performance is augmented when there are greater levels of stakeholder integration. The third topmost ranked DF in this study is social capital. Social capital may be established from managerial networking and social interactions with top managers at other firms, political leaders, bureaucratic officials, and leaders of communities, and it can augment a firm’s performance (Acquaah, 2007) [11] .

The ranks of the sets of DFs for effective stakeholder management and performance of SMEs within each dimensional context of the inquiry are presented in the subsections of this section. The DFs for effective stakeholder management and performance of SMEs within the macro, meso and micro dimensions were ranked according to their significance as evinced by the results of the study.

The results of this study affirms stakeholder theory (Freeman, 1984) [3] , with regards to how an important component of value creation in businesses, which amplifies their prospects of being effective, is their engagement and development of strong relations with a wide range of stakeholders (Harrison, Bosse, & Phillips, 2010 [21] ; Pollack, Barr, & Hanson, 2017 [23] ; Sefiani et al., 2018 [24] ). Theoretically, the findings of the study substantiate literature (Voss, Sirdeshmukh, & Voss, 2008 [29] ; Amankwah-Amoah, Danso, & Adomako, 2019 [43] ; Desai, 2018 [48] ; Acquaah, 2007 [11] ) that, besides financial slack, stakeholder integration and social capital are critically imperative for effective stakeholder management and performance of SMEs. The theoretical framework based on the macro, meso and micro models helps in understanding the crucial precincts that, when concentrated on, can proliferate effective stakeholder management and performance of small- and medium-sized firms. Also, this study theoretically sanctions an upsurge in the level of difference revealed on the driving factors for effective stakeholder management and performance of SMEs, symptomatically, by using the BWM through the lens of stakeholder theory over the macro, meso and micro dimensional contexts. Practically, the results of this research would provide valuable guidelines for SME managers, stakeholders and practitioners in the industry during strategic decision making.

Concisely, this study substantiates research on the driving factors for effective stakeholder management and performance of SMEs. However, the method and context used in this work is different from other published works on the subject in extant literature. A theoretical framework underpinned by stakeholder theory, and based on the macro, meso and micro dimensional contexts was used to study the driving factors for effective stakeholder management and performance of SMEs in Ghana. This theoretical framework may be applied by any SME to catalogue its organizational driving factors with respect to their degrees of significance.

By virtue of this research, SME managers are presented with an all-inclusive and profound overview of the driving factors for effective stakeholder management and performance of their firms. The study is particularly helpful to managers of SMEs in developing countries such as Ghana, Ivory Coast, Liberia, Nigeria, and other ambitious developing economies in Africa. SME managers can adopt the theoretical framework developed in this study, and commit more resources towards identified and significantly rated driving factors for effective stakeholder management and performance of their firms.