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Government incentives are critical for successful indigenous innovation commercialisation, yet there are concerns about the efficacy of these incentives. Therefore, this study examines the effectiveness of government incentives on successful indigenous innovation commercialisation in the context of low-income economies by testing the effects of demand and supply-side incentives on firm performance in the small-scale industry in Ghana.

The theoretical framework for this study is built on the below-the-radar theory of innovation (Kaplinsky et al., 2009). Using a sample of 557 firms engaged in commercialising various indigenous innovations in the small-scale industry in Ghana, PLS-SEM was deployed to assess 11 hypothesised paths based on a validated questionnaire.

The model results, at a 5% significance level, indicate that supply-side incentives are statistically insignificant on sales and profitability but have significant positive effects on employment. The direct and moderating influence of supply-side incentives and market factors on overall firm performance is also insignificant, while demand-side incentives to buyers have significant positive effects on all the performance metrics and positively moderate the effects of market factors.

The research focused on commercialising indigenous innovation in the context of low-income economies. Few studies, if any, have separately explored the effect of demand and supply-side government incentives on indigenous innovation in the context of low-income economies. The findings suggest that innovation support should focus more on the demand side of the innovation value chain.

The digital transformation is dramatically changing the business-to-business (B2B) sales environment, challenging long-standing views regarding the critical competencies required of salespeople. This paper aims to explore the personal traits associated with sales performance in a digital selling environment.

Using template analysis, the researchers captured and coded over 21 h of in-depth, semi-structured interviews with senior sales leaders from various industry sectors, exploring their perceptions of the personal traits now required of B2B salespeople in the digital landscape.

The research identifies three high-level trait types critical to sales success within a digital selling environment: “analytical curiosity” – the natural motivation and ability to gather and synthesize sales-related knowledge, “empathetic citizenship” – the ability to establish initial rapport while building long-term trust and “disciplined drive” – the exertion of selling effort in a highly focused and methodical manner across all stages of the sales process.

The present data came from interviews with sales leaders in Canada. A more global sample may lead to additional insights. Moreover, the sample was drawn from long-cycle B2B sales environments; conclusions may differ for short-cycle or business-to-consumer markets.

This paper presents a framework for hiring and developing salespeople in the digital sales environment, identifying personal trait types that sales leaders should look for when hiring: analytical curiosity, empathetic citizenship and disciplined drive. The paper identifies how these trait types influence sales success, suggesting that sales leaders could coach and educate their teams to make the best use of them.

This paper presents a conceptual framework for hiring in the digital sales environment and introduces the trait of analytical curiosity not previously discussed in the literature.

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 non-fungible token (NFT) market had undergone dramatic growth and a sudden decline during 2021–2022. The market experienced a surge in prices in late 2021 and early 2022, with NFTs being sold at inflated prices. Despite this, by April 2022, the market underwent a correction, and the prices of NFTs returned to more reasonable levels. This can be a result of imitating the actions or judgments of a larger group, which is not systematically proven yet. Therefore, this study systematically investigates the applicability of herding behavior in the NFT market.

This research employs cross-sectional absolute deviation (CSAD) of returns and ordinary least squares (OLS) to test herding behavior with moving time windows of 10, 20 and 30 days based on the sales data collected from public interface of OpenSea between July 1, 2021 and June 30, 2022. Additionally, NFT-related keyword usage analysis is done for the detected herding periods.

As per the results of the data analyzed, herding behavior was evidenced using 10-, 20- and 30-day time windows from July 1, 2021 to June 30, 2022because of media movement. The findings revealed that this behavior was present and aligned with the overall behavior of the market.

This study introduces CSAD to examine herding behavior patterns within the NFT market. Complementing this method, keyword count-based analysis is employed to identify the underlying causes of herding behavior. Through this comprehensive approach, this study not only uncovers the roots of herding behavior but also offers an assessment of the time windows during which it occurs, considering the plausible socioeconomic contexts that influence these trends.

This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations.

The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes.

The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process.

This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.

With the goal of helping consumers bounce back from the financial challenges they faced as a result of the COVID-19 pandemic, many firms developed and announced consumer-targeted resiliency programs (e.g. Walgreens waived delivery fees, Associated Bank allowed deferred mortgage payments). However, there is a paucity of research examining the unique features of these programs, and whether firms' investors (the first external stakeholder group to provide them with feedback regarding their strategies) were receptive to these programs during a period of time in which firms themselves were suffering financially. Drawing on resilience theory and stakeholder theory, the present research incorporates an event study of consumer-targeted resiliency program announcements to understand their financial implications for firms, and to learn whether firms witnessed different financial effects as a result of firm- and program-specific factors.

This study referred to business news publications and newswire services to collect a comprehensive list of consumer-targeted resiliency programs announced by publicly traded U.S. firms during the pandemic. The resulting dataset consisted of 145 announcements made during the period of February–June 2020. An event study was conducted in order to precisely measure the main effect of consumer-targeted resiliency programs on firm value, as manifested through abnormal stock returns. Finally, a moderation analysis (regression) was conducted to uncover whether firm characteristics or specific features of firms' consumer-targeted resiliency programs lead certain firms to witness stronger financial effects than others.

The main effect of consumer-targeted resiliency programs on firm value was found to be positive – a 1.9% increase on average. The moderation analysis finds that non-financial firms were rewarded more positively than financial firms (e.g. banks and credit card companies). In addition, financial aid (i.e. allowing customers to defer their payments to a firm for its products/services, versus a reduction in the price of a product/service or offering it for free or giving cash back to customers) and temporal characteristics (i.e. an offer being framed as limited-time, vs being indefinite or for the foreseeable future) are not found to have a moderating effect.

This theory-driven empirical study uncovers practical implications for managers of firms interested in whether investing in corporate social responsibility during times of crisis is a wise allocation of resources. Any form of financial aid for consumers, regardless of temporal limitations, is received positively by investors.

As a response to the increased frequency of disruptive events and intense competition, organizational agility has become a key concept in organizational research. Fostering organizational agility requires leveraging knowledge that exists both outside (exploration) and inside (exploitation) the organization. This research tests the so-called ambidexterity hypothesis, which claims that a balance between exploration and exploitation leads to increased organizational outcomes, including the development of organizational agility. Complementing previously established measurement models on ambidexterity, this research proposes an alternative measurement model to analyze how ambidexterity can enhance organizational agility and, indirectly, performance, taking into consideration the moderating effect of environmental competitiveness.

A review of existing measurement models for ambidexterity shows that tension, a crucial aspect of ambidexterity, is often neglected. The authors, therefore, develop a new measurement model of ambidexterity to incorporate ambidexterity-induced tension. Using this measurement model, they examine the effect of ambidexterity on the development of entrepreneurial and adaptive agility as well as performance.

Ambidexterity positively influences both entrepreneurial and adaptive agility, indicating that a balance between exploration and exploitation has superior organizational effects. This finding confirms the ambidexterity hypothesis with respect to organizational agility. Furthermore, both entrepreneurial and adaptive agility drive organizational performance. These two indirect effects via agility fully mediate the impact of ambidexterity on organizational performance. Finally, environmental competitiveness positively moderates the relationship between ambidexterity and adaptive agility.

The findings extend research on ambidexterity by showing its positive effects on organizational agility. Furthermore, the study proposes an alternative operationalization to capture the ambidexterity construct that may lay the groundwork for further applications of the ambidexterity concept.

This study investigates whether logistics and supply chain resilience strategies (SCREST) can help mitigate the negative impacts of disruptions on firm performance and logistics and supply chain (SC) activities of companies, using the COVID-19 pandemic as a case study.

The authors collected primary data on the implementation of different types of SCRESTs and measured the impact of COVID-19 in terms of firm performance and logistics and SC metrics through a survey of Japanese manufacturing companies in four sectors. The authors used these data to illustrate whether the companies benefitted from SCRESTs in mitigating the negative impacts of COVID-19. A questionnaire comprising structured and open-ended questions was sent to 8,000 companies all over Japan that met the selection criteria, using a combination of mail and web-based media. The respondents were logistics and SC professionals. A combination of qualitative and quantitative analysis was performed for data analysis and interpretation.

Research conducted within the case of the Japanese context revealed that findings varied depending on the methodology applied. The use of a direct analysis approach and qualitative analysis suggested that the implementation of SCRESTs is beneficial in addressing the negative impacts of COVID-19 on firm performance and logistics and SC activities, whereas the application of indirect analysis approach yielded mixed results. The analysis also indicated a shift in the preferred SCRESTs during COVID-19.

To the best of the authors’ knowledge, this is the first study to examine the benefits of implementing SCRESTs using primary data from the manufacturing sector of Japan. Furthermore, empirical research on this topic is generally lacking.

This study examines whether different strategy archetypes deploy specific performance metrics to support their strategic goals and priorities. If so, does alignment of strategy and metrics positively impact organisational performance?

The conceptual framework and hypotheses are couched in Contingency Theory. The role of business strategy as a moderating variable is tested using MANOVA, followed by post hoc pairwise comparisons. The results are based on cross-sectional survey data from 372 manufacturing and service organisations in Italy.

The overall contingency effect of business strategy in selecting and deploying performance metrics and their effect on organisational performance is supported. However, the group-wise post hoc analyses show support only for Prospectors but not for Defenders and Analysers.

This research lends further support in favour of the Contingency Theory from a new geographic context (Italy) that there are no universally best performance metrics that drive organisational performance. However, more research is needed to understand why the theory only holds for certain strategic archetypes and not across all archetypes.

Managers can direct resources and effort towards designing and deploying the “right” type of performance metrics suitable for their strategic orientation and thus optimise organisational performance.

This is a rare study that tests the moderating role of business strategy using all four strategic archetypes of the Miles and Snow typology. It deploys both financial and non-financial measures and uses a very large sample of both manufacturing and service organisations from a relatively unexplored region of the world. The study provides additional evidence in favour of the Contingency Theory whilst advocating for more research to refine our understanding of why the contingency perspective is not so important for firms that are not the first-in.

This study analyzes how tech firms can implement the modern wave of subscription-based business model (SBBM), including value proposition, value creation, value capture and performance. In fact, these elements push tech firms to move from traditional to SBBMs.

To achieve the objectives of this study, we initially construct a theoretical framework for applying SBBM. Subsequently, we employ qualitative research to examine the current implementation of the subscription-based economy within tech firms.

A successful SBBM necessitates capturing value through sustainable revenue transactions and revising aspects of the value proposition, creation and capture. Continuous improvement through business value analysis is imperative. Additionally, an agile operations system is vital to address revenue complexities, enable data collection and enhance value proposition, service innovation, churn rate and customer retention, which are essential for SBBM maintenance.

This study delves into how the subscription-based economy is reshaping the business models of tech firms. Beyond exploring the theoretical foundation of this transformative path, this study offers actionable insights on enhancing the value proposition, creation, capture and business value within subscription-based economy frameworks.