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The purpose of this paper is to investigate the impact of customer-focus on small medium enterprise (SME) performance from the perspective of a resource-based view (RBV).

This research study implemented a survey strategy to gather data from 255 respondents on the registered list of Ghana Enterprise Agency (GEA) in the eastern region of Ghana. Scales used to gather data were operationalized from previous research studies. A structural equation modeling (SEM) path analysis was used to estimate the impact of customer-focus on the performance of SMEs.

The outcomes of this study indicate that customer-focus has a significant positive impact on SME performance, hence backing the current demand for investigating the distinct influence of customer-focus on SME performance. The results show that customer-focus has a positive and significant relationship with financial performance, customer performance, internal business process performance and learning and growth performance, thus supporting the literature on the positive impact of customer-focus on SME performance. Therefore, customer-focus determinants used in this study, including co-creation, networking ties, customer insight and artificial intelligence marketing (AIM), are critical to the optimization of SME performance.

Notwithstanding the importance of this research study mentioned earlier, the study has limitations. Notably, the sample size of this study can be increased to capture SME respondents in other geographical zones that were not included in this study. Future research studies may address how business environment conditions moderate the relationship between customer focus and performance, and also the cause-effect of the relationship between customer focus and business environment conditions on SME performance.

The practical implications consist of two main items. First, this study empowers SME owners and managers to develop a customer focus technique as a central strategic goal in their quest for SME performance optimization. Second, SME owners and managers should progressively exploit the four determinants of customer focus which include co-creation, networking ties, customer insight and (AIM in order to accrue important resources for effective utilization of their customer focus competences as a way to enhance their performance.

This study is targeted at the sound development of SMEs to bring about poverty alleviation and employment. Poverty, unemployment and poor living standards are recognized as vital social challenges in most emerging economies. The establishment of customer focus as an important strategic capability provides opportunities for SME survival, profitability and growth.

Generally, the findings of this research study provide a strong backing to RBV perspective and the proposition that customer-focus and its determinants (i.e. co-creation, networking ties, customer insight and AIM) should be acknowledged as a vital strategic resource for optimizing the performance of SMEs. This research study also provides new knowledge contribution to the present body of knowledge on customer-focus orientation and management literature, particularly in the context of an emerging economy.

The aim of this study is to empirically investigate the impact of marketing analytics capability on business performance from the perspective of RBV theory.

This study used a survey method to gather information from 225 food processing SMEs registered with the Ghana Enterprise Agency (GEA) in Ghana’s eastern region. A structural equation modeling (SEM) path analysis was used to assess the impact of marketing analytics capability (MAC) on the performance of SMEs.

The results of the study show that MAC significantly and positively affect the financial performance (FP), customer performance (CF), internal business process performance (IBPP) and learning and growth performance (LGP) of Ghanaian SMEs. The findings of this study also illustrated the significance of MAC determinants, including marketing analytics skills (MAS), data resource management (DRM) and data processing capabilities (DPC), in achieving SME success in Ghana.

The research’s conclusions give RBV theory strong credence. The results of this study also provide credence to previous research finding that SMEs should view MAC and its determinants (i.e. DRM, DPC, MAS) as a crucial strategic capability to improve their performance (i.e. FP, CF, IBPP, LGP). With regard to its contribution, this study broadens the body of knowledge on MAC and SME performance, particularly in the context of an emerging economy.

The purpose of this paper is to explore the role of the entrepreneur in the knowledge transfer (KT) process of a start-up enterprise and the ways that role should change during the development phase to ensure mid-term business survival and growth.

An in-depth, qualitative case study of Birra Flea, an Italian Craft Brewery, is presented and analysed using Liyanage et al.’s (2009) framework to identify the key components of the KT process, including relevant knowledge, key actors, transfer steps and the criteria for assessing its effectiveness and success.

The entrepreneur played a fundamental and crucial role in the start-up process, acting as a selective and passionate broker for the KT process. As Birra Flea matures and moves into the development phase, the role of the entrepreneur as KT’s champion needs to be integrated and distributed throughout the organisation, with the entrepreneur serving as a performance controller.

This study enriches the knowledge management literature by applying a framework designed to provide a general description of KT, with some modifications, to a single case study to demonstrate its effectiveness in differentiating types of knowledge and outlining how KT can be configured to support essential business functions in an SME.

The analysis systematises the KT mechanisms that govern the start-up phase of an award-winning SME, with suggestions for how to manage KT during the development phase. Seldom are practitioners given insight into the mechanics of a successful SME start-up; this analysis serves as a practical guide for those wishing to implement effective KT strategies to emulate Birra Flea’s success.

The world’s economy thrives on SMEs, yet many fail as start-ups before they even have a chance to reach the development phase, presenting a motivation to study the early stages of SMEs. This study addresses that gap with an in-depth theoretical analysis of successful, effective KT processes in an SME, along with practical implications to enhance the knowledge, experience and skills of the actors that sustain these vital economic enterprises.

The purpose of this study was to demonstrate a cloud business intelligence model for industrial SMEs. An initial model was developed to accomplish this, followed by validation and finalization of the cloud business intelligence model. Additionally, this research employs a mixed-techniques approach, including both qualitative and quantitative methods. This paper aims to achieve the following objectives: (1) Recognize the Cloud business intelligence concepts. (2) Identify the role of cloud BI in SMEs. (3) Identify the factors that affect the design and presenting a Cloud business intelligence model based on critical factors affecting SMEs during pandemic COVID-19. (4) Discuss the importance of Cloud BI in pandemic COVID-19 for SMEs. (5) Provide managerial implications for using Cloud BI effectively in Iran’s SMEs.

In the current study, an initial model was first proposed, and the cloud business intelligence model was then validated and finalized. Moreover, this study uses a mixed-methods design in which both qualitative and quantitative methods are used. The fuzzy Delphi Method has been applied for parameter validation purposes, and eventually, the Cloud business intelligence model has been presented through exploiting the interpretive structural modeling. The partial least squares method was also applied to validate the model. Data were also analyzed using the MAXQDA and Smart PLS software package.

In this research, from the elimination of synonym and frequently repeated factors and classification of final factors, six main factors, 24 subfactors and 24 identifiers were discovered from the texts of the relevant papers and interviews conducted with 19 experts in the area of BI and Cloud computing. The main factors of our research include drivers, enablers, competencies, critical success factors, SME characteristics and adoption. The subfactors of included competitors pressure, decision-making time, data access, data analysis and calculations, budget, clear view, clear missions, BI tools, data infrastructure, information merging, business key sector, data owner, business process, data resource, data quality, IT skill, organizational preparedness, innovation orientation, SME characteristics, SME activity, SME structure, BI maturity, standardization, agility, balances between BI systems and business strategies. Then, the quantitative part continued with the fuzzy Delphi technique in which two factors, decision-making time and agility, were deleted in the first round, and the second round was conducted for the rest of the factors. In that step, 24 factors were assessed based on the opinions of 19 experts. In the second round, none of the factors were removed, and thus the Delphi analysis was concluded. Next, data analysis was carried out by building the structural self-interaction matrix to present the model. According to the results, adoptability is a first-level or dependent variable. Regarding the results of interpretive structural modeling (ISM), the variable of critical success factors is a second-level variable. Enablers, competencies and SME characteristics are the third-level and most effective variables of the model. Accordingly, the initial model of Cloud BI for SMEs is presented as follows: The results of ISM revealed the impact of SME characteristics on BI critical success factors and adoptability. Since this category was not an underlying category of BI; thus, it played the role of a moderating variable for the impact of critical success factors on adoptability in the final model.

Since this study is limited to about 100 SMEs in the north of Iran, results should be applied cautiously to SMEs in other countries. Generalizing the study's results to other industries and geographic regions should be done with care since management perceptions, and financial condition of a business vary significantly. Additionally, the topic of business intelligence in SMEs constrained the sample from the start since not all SMEs use business intelligence systems, and others are unaware of their advantages. BI tools enable the effective management of companies of all sizes by providing analytic data and critical performance indicators. In general, SMEs used fewer business intelligence technologies than big companies. According to studies, SMEs understand the value of simplifying their information resources to make critical business choices. Additionally, they are aware of the market's abundance of business intelligence products. However, many SMEs lack the technical knowledge necessary to choose the optimal tool combination. In light of the frequently significant investment required to implement BI approaches, a viable alternative for SMEs may be to adopt cloud computing solutions that enable organizations to strengthen their systems and information technologies on a pay-per-use basis while also providing access to cutting-edge BI technologies at a reasonable price.

Before the implementation of Cloud BI in SMEs, condition of driver, competency and critical success factor of SMEs should also be considered. These will help to define the significant resources and skills that form the strategic edge and lead to the success of Cloud BI projects.

Most of the previous studies have been focused on factors such as critical success factors in cloud business intelligence and cloud computing in small and medium-sized enterprises, cloud business intelligence adoption models, the services used in cloud business intelligence, the factors involved in acceptance of cloud business intelligence, the challenges and advantages of cloud business intelligence, and drivers and barriers to cloud business intelligence. None of the studied resources proposed any comprehensive model for designing and implementing cloud business intelligence in small and medium-sized enterprises; they only investigated some of the aspects of this issue.

An efficient policy supporting clustered business operations necessitates an appreciation of the dynamics of rivalry and collaborations among businesses. This paper postulates that variation in competition and cooperation can significantly influence the nature of business relationships among clustered businesses, which is essential for cluster policy particularly (Newlands, 2003) as most research on rivalry and cooperation in clusters have been in developed economies. The purpose of this paper is to seek to fill the gap in the literature in African clusters based on original empirical research.

The study adopts a mixed-method research design allowing for data triangulation to study two food processing clusters. The approach comprises a survey and in-depth interview with key actors along the supply chain.

The findings show that business clusters with more formal business structures tend to have minimal horizontal competition but higher vertical cooperation. Comparatively, clusters with more socially embedded milieu tend to have higher levels of cooperation and minimal competition in both vertical and horizontal relationships. The research also shows that such variations in inter-business relationships have an effect on cluster operations in terms of business access to finance, formal contract, sharing of innovation and the way they relate to different stakeholders in their supply chain.

This paper advances a critical case for international business theory on clusters in Africa to incorporate the distinctive business relationships in small and medium enterprises (SME) clusters. It also demonstrates how unique location-specific attributes of developing economies hold the key to sustaining the operations of SME-based clusters.

This paper aims to develop a process model of business-to-business (B2B) relationship recovery after a transgression has placed the future of the relationship in doubt. The research questions ask, How are relationships recovered? and How does the relationship strength pre-transgression influence the recovery process?

The process model is empirically grounded with first-hand narratives of owner managers (OMs) and key personnel of Irish small and medium-sized enterprises (SMEs). Using the critical incident technique, 25 owner and manager interviews in 23 SMEs resulted in 48 recovery narratives.

The findings identify four types of outcomes flowing from two potential recovery process paths. The strength of the relationship pre-transgression and the desire to maintain the relationship influence the parties’ actions during the recovery process and the status of the relationship subsequently.

The authors acknowledge that each narrative in the data are the informants’ construction of the phenomenon. The B2B relationship recovery process model offers OMs and SMEs a blueprint of what to expect, and how they might reach for recovery instead of the relationship ending.

Prior studies either treat recovery as a minor part of an ending process or focus on a single sub-process, leaving the overall process under-researched. This study contributes to the B2B relationship dynamics discussion with a processual view of the overall recovery process, including recovery sub-processes, paths and temporal outcomes in different types of relationships and takes into account the pre-transgression relationship.

The purpose of this paper is to explore how employees in small and medium-sized enterprises (SMEs) practise and view workplace learning at three different life-cycle stages.

It is a qualitative study using a sample of 30 Hong Kong SMEs classified into inception, high-growth or maturity stage, from which firms in each stage were randomly selected and interviewed until data saturation was reached. Snowball sampling was adopted during interviews and data were examined through thematic analysis.

Consistent themes (patterns) from 134 semi-structured interviews are identified, addressing both similarities and differences in the nature of the practice of workplace learning in SMEs between life-cycle stages.

More similar comparative studies in other parts of the world, including quantitative surveys on larger samples, with either SMEs or multinational corporations, are encouraged to enrich the current findings.

If organisational growth is a priority, SME owner/managers should support employees’ work and learning in a timely fashion. As the study finds, individual learning and inter-organisational learning are considered “a must to have” for employees, regardless of which stage the firm is at. When an SME enters high-growth, however, more opportunities for group learning are particularly beneficial. For mature SMEs, it is essential for learning to move towards systemisation and include a professional development component to meet employees’ career expectations, not just their work demands.

The results advance the body of knowledge in SME learning from the life-cycle perspective. As one of the first studies in bridging these areas, it brings new implications to academic researchers and SME practitioners.

This chapter examines the interactions of formal and informal forms of small and medium-sized enterprise (SME) business support, characterised as interactions within an ‘enterprise industry’. An analysis of the interactions revealed in the existing literature for different forms of business support develops a new conceptual framework for understanding those varied forms of external influence targeted at SMEs that constitute and extend a ‘patchwork quilt’ of provision. This chapter focusses on how different forms of support and advice interact, the centrality of state influence and how such interactions can be considered part of a firm’s regulatory context. This conceptualisation allows the consideration of both business support and state regulations to move beyond conceptions of positive or negative impacts on factors such as firm growth. Instead, it establishes a conceptual lens for considering how the different forms of external influence can shape the practices and attitudes of SMEs and their owner-managers. Policy makers and organisations within the enterprise industry seeking to develop effective forms of support or regulation should not consider such activities in isolation or in simple, decontextualised positive or negative terms.

This paper seeks to investigate the key drivers and barriers of adopting mobile customer relationship management (mCRM) services in small‐ and medium‐sized enterprises (SMEs) and proposes an mCRM strategy framework.

Previous SME technology adoption literature has used different models to explain how SMEs accept or reject technology innovations. There is a lack of research in mobile technologies such as mCRM services. Using a secondary research method, this study critically analyses the impact of mCRM services adoption by UK SMEs.

Rapid development in mCRM applications enables SMEs to gain competitive advantages. This paper argues that mCRM services help SMEs to create different levels of relationship bonds with their customers, which in turn can create value proposition and improve business performance.

This study suggests that SME owners/managers need to understand their business needs and processes, and the mobile technology, to focus on their CRM strategies, and allocate resources in order to successfully adopt mCRM services to exploit the full potential. The conceptual model needs to be tested empirically.

This study demonstrates that business values and core services can be specific to mCRM strategy. It proposes and discusses the theoretical and practical implications of the mCRM strategy framework and suggests further research directions.

This study examines how three psychological factors (i.e. perceived experience quality, perceived similarity and client participation) that impact client evaluations of their recent audit experiences influence client satisfaction and trustworthiness, which, in turn, affect advocacy in an small- and medium-sized enterprise (SME) context. Furthermore, the study investigates whether the influence of the three psychological factors on client satisfaction and trustworthiness is contingent on client expertise.

The sample consisted of 744 SME executives from the following four regions: central, northern, eastern and southern Thailand. Data were collected using a survey questionnaire. Confirmatory factor analysis was conducted to ensure the reliability and validity of the scale before structural equation modeling was applied to analyze the data.

The results showed significant positive effects of the three psychological factors (perceived experience quality, perceived similarity and client participation) on client satisfaction and perceived trustworthiness. The moderating role of client expertise on the relationships is also found. More specifically, client expertise positively moderated the connections between experience quality and satisfaction, experience quality and trustworthiness and client participation and trustworthiness. Conversely, client expertise negatively moderated the similarity–satisfaction and similarity–trustworthiness relationships.

This study contributes to the audit literature by examining the role of psychological factor that impacts client satisfaction and perceived trustworthiness in the SME context. Moreover, the moderating role of client expertise is examined for the first time, providing new insights into the boundary condition of the relationship.