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This study aims to investigate the comprehensive conceptualization how digital marketing and its adoption increase the productivity of small and medium-sized enterprises (SMEs), as well as the impact of technological orientation, customer relationship management and digital marketing on SMEs’ business performance in emerging markets (EMs).

Anchored by social network theory, 178 SMEs were conveniently drawn from the National Board for Small Scale Industries now Ghana enterprise agencies in Ghana. The hypotheses were analysed using the SPSS package tool, and structural equation modelling was used, as well.

This study reveals that the conceptualization and adoption of digital marketing positively affect the performance of SMEs’ business management in EMs. In addition, a positive moderating effect of dynamism is observed in the relationship between digital marketing and SMEs’ business performance.

This study focuses only on SMEs from the Greater Accra and Ashanti regions of Ghana as an EM, and it proposes priorities for future research streams in both developed and emerging countries.

The findings encourage SMEs to develop quality digital marketing technologies, good customer relationships and technological orientation and customer relationship management competencies in EMs to maximise profit.

This paper fills considerable knowledge, evidence and contextual gaps in the literature on SMEs, entrepreneurship and marketing in EMs by presenting a comprehensive overview of how SMEs can use digital marketing in an EM context to achieve the following: customer acquisitions, satisfaction and retention; increased profitability; quality service delivery; value creation; and cost reductions.

Knowledge sharing is critical to creating value in platform ecosystems. However, participants refrain from sharing knowledge and even engage in free-riding behavior, thereby causing the value co-destruction of the platform ecosystems. To encourage knowledge sharing among participants, it is essential to analyze the influencing factors and decision-making mechanisms of knowledge sharing in the platform ecosystems.

The study investigated the issue of knowledge sharing among participants in platform ecosystems, based on the stochastic differential game model. Considering the uncertain factors, the Nash non-cooperative game, Stackelberg leader-follower game, and cooperative game models were proposed. By utilizing system dynamics and numerical simulations, the key influencing factors and mechanisms of knowledge sharing were deeply explored, consequently providing game solutions to achieve the Pareto optimality of the ecosystem.

Participants' innovation capability and the marginal benefits of knowledge-sharing positively impact knowledge-sharing decisions, while the environmental knowledge decay rate has a negative influence. The platform subsidy mode enhances the knowledge-sharing effect, and the collaborative cooperation mode can realize the Pareto optimization of the system.

The research findings will provide theoretical support for fostering knowledge innovation and sustainable development of platform ecosystems. Managers should cultivate an innovative environment, establish fair reward mechanisms, and utilize subsidies to promote knowledge sharing, leading to higher value creation.

Utilizing the stochastic differential game model, the study proposed various game-theoretic frameworks to analyze participants' knowledge-sharing strategies. The integration of system dynamics and numerical simulations provides a practical approach to understanding the key influencing factors and decision-making processes.

The purpose of this study was to provide comprehensive overview, and exposure of the correlation between entrepreneurial orientation dimension (EOD) and business innovation environment (BIE) on small and medium enterprises (SMEs) financial performance in the Ghanaian manufacturing SMEs sector that enhances knowledge and contextualization in marketing and entrepreneurship literature.

Anchored on resource-based view theory, 520 manufacturing SMEs companies were conveniently drawn from Association of Ghana Industry, through National Board for Small Scale Industries, using structural equation modelling techniques to analyse the hypotheses.

This study revealed that three entrepreneurial orientation dimensions EOD: risk-taking, innovations and pro-activeness have positive significant impact on financial performance manufacturing of SMEs. BIE also has positive impact on financial performance of manufacturing of SMEs and BIE moderates SMEs financial performance.

This is a country-specific manufacturing SMEs sector, which means that the findings cannot be used to justify other SMEs in Ghana and SMEs in different country. However, the study was limited to only three EODs: risk-taking, innovations, pro-activeness and Ghanaian manufacturing BIE of SMEs. More countries and other SMEs are needed to expand the field of research in EODs and BIE.

It provides an insight into BIE which is important for marketers, entrepreneurs, regulatory bodies, SMEs owners-managers, directors, government and NGO to strengthening and reshaping their BIE in manufacturing SMEs sector policies, conducts and laws.

This paper fills knowledge and contextual gap in entrepreneurship and marketing literature by presenting comprehensive overview of BIE and EOD research that enhances the on-going discussion in the marketing and entrepreneurship manufacturing SMEs context and proposing priorities for future research streams within an emerging economy.

Small and medium enterprises (SMEs) do not need only traditional marketing strategies in the dynamic business environment of the manufacturing sector. Entrepreneurial marketing dimension (EMD) is an alternative marketing approach for SMEs. Therefore, this paper aims to investigate whether EMD innovation has a positive and significant effect on SMEs performance on Ghanaian Halal food and beverages.

Correlative descriptive research method was used and 432 questionnaires with five-point Likert scale were distributed among owners-managers of manufacturing sectors of Ghanaian Halal food and beverages SMEs producers were chosen by a simple random sampling method. Structural equations modelling structural equations modelling techniques was used to analyse data.

The result of data analysis indicates a positive and significant effect of EMD on manufacturing SMEs performances of Halal food. Nevertheless, the effect of EMD on the production performance of the aforementioned companies is confirmed positive. The findings also show that production performances of Halal food SMEs result in their financial performance.

The study’s sample is limited to Halal food SMEs manufacturing in Ghana. More research can be done investigating this relationship from different sectors and in Islamic and non-Islamic countries.

This research implies that Halal food SMEs manufacturing producers in a country is imperative in Muslim-minority countries. This study gives a benchmark for the non-Muslim-majority countries which endeavour to embark on the Halal SMEs manufacturing food. Muslim-minority countries that envision to succeed in the global Halal market could emulate Ghana’s approach in branding itself as a recognised non-Muslim-majority country in producing Halal foods. This can be done by implementing innovative, proactive, opportunist, risk-taking and customer-oriented initiatives to achieve better market and innovative performances and higher profits.

This paper fills a knowledge gap by presenting the first comprehensive overview of Halal food SMEs manufacturing performance research that enhances the ongoing discussion in hospitality, entrepreneurship and marketing fields in Islamic and non-Islamic contexts.

Intelligent prediction of node localization in wireless sensor networks (WSNs) is a major concern for researchers. The huge amount of data generated by modern sensor array systems required computationally efficient calibration techniques. This paper aims to improve localization accuracy by identifying obstacles in the optimization process and network scenarios.

The proposed method is used to incorporate distance estimation between nodes and packet transmission hop counts. This estimation is used in the proposed support vector machine (SVM) to find the network path using a time difference of arrival (TDoA)-based SVM. However, if the data set is noisy, SVM is prone to poor optimization, which leads to overlapping of target classes and the pathways through TDoA. The enhanced gray wolf optimization (EGWO) technique is introduced to eliminate overlapping target classes in the SVM.

The performance and efficacy of the model using existing TDoA methodologies are analyzed. The simulation results show that the proposed TDoA-EGWO achieves a higher rate of detection efficiency of 98% and control overhead of 97.8% and a better packet delivery ratio than other traditional methods.

The proposed method is successful in detecting the unknown position of the sensor node with a detection rate greater than that of other methods.