Despite the considerable hype about how Big Data Analytics (BDA) can transform businesses and advance their capabilities, recognising its strategic value through successful adoption is yet to be appreciated. The purpose of this paper is to focus on the process-level value-chain realisation of BDA adoption between SMEs and large organisations.
Resource-based theory offered the lens for developing a conceptual BDA process-level value chain adoption model. A combined two-staged regression-artificial neural network approach has been utilised for 369 small, medium (SMEs) and large organisations to verify their critical value chain process-level drivers for successful organisational adoption of BDA.
The findings revealed that organisational BDA adoption success is driven predominantly by product—and service-process-level value, with distinctive discrepancies dependent on the organisation’s size. Large organisations primarily embrace BDA for their external value chain dimensions, while SMEs encompass its internal value chain cues. As such, businesses will be advised to acknowledge their organisational dynamics and precise size to develop the right strategies to adopt BDA successfully.
The study advances the understanding of the role of internal and external value chain drivers in influencing how BDA can be successfully adopted in SMEs and large organisations. Thus, appreciating the organisation’s unique attributes, including its size, will need to be carefully examined. By investigating these elements, this research has shed new light on how developing such innovative capabilities and competencies must be carefully crafted to help create a sustainable competitive advantage.
For an organisational positioning, acknowledging the role of internal and external value chain drivers is critical for implementing the right strategies for adopting BDA. For larger businesses, resources for innovation often can be widely available compared to SMEs. As such, they can manage their costs and associated risks resourcefully. By considering the identified value-chain-related adoption success factors, businesses should be better positioned to assess their competencies while being prepared to adopt BDA.
The study offers the research and business community empirical-based insights into the strategies needed to successfully adopt big data in an organisation from a process-level value chain perspective.
This paper aims to examine the direct impacts of marketing resources and marketing activities on several business performance indicators in the banking industry and the indirect effects through customer-based brand equity.
We use a holistic empirical approach based on resource-based view and marketing productivity chain. The main study consists of a secondary analysis using quarterly data of fourteen banks over four years. We analyze the data using fixed-effect panel data regression, namely seemingly unrelated regressions.
We find that customer-based brand equity is one of the most influential factors on business performance. Moreover, the indirect effect through customer-based brand equity should be considered in improving business performance. Marketing-related financial resources positively impact customer-based brand equity and business performance. Regarding marketing activities, pricing strategies affect the bank preferences of customers, which in turn affect the growth of deposit volumes and churn rates. Additionally, the number of bank branches positively impacts business performance. Advertising spending on different media has differentiated impacts on the performance indicators; thus, the allocation of advertising budget and advertising planning are critical.
This study examines the inter-relationships among marketing resources, marketing activities, consumer response through brand equity and marketing performance. This study contributes to the literature by integrating the resource-based view and the marketing productivity chain to analyze the inter-relationships using panel data and several sector-related metrics. This study provides valuable insights to decision-makers in the banking industry.
The present study investigates the impact of supply chain disruption orientation (SCDO) on four supply chain disruption (SCD) mitigation strategies: supply chain integration (SCI), supply chain agility (SCA), supply chain visibility (SCV) and supply chain redundancy (SCR). It also examines the impact of the four mitigation strategies on SCD. The impact of the latter on business performance (BP) is also explored.
This study employs an empirical approach through survey research methodology. It analyzes data collected from 304 managers from pharmaceutical distribution companies in Jordan. Appropriate validity and reliability tests were employed for the study constructs. Path analysis using AMOS software was performed to test the study hypotheses.
SCDO was found to positively affect all SCD mitigation strategies. Furthermore, among the four mitigation strategies examined, SCV exhibited the highest significant impact in reducing SCD, followed by SCA and then SCR. However, the results revealed that SCI did not significantly impact SCD. Additionally, SCD proved to be negatively and significantly related to BP.
The present study fills a gap in the literature regarding the management of SCDs in pharmaceutical supply chains (SCs) generally and SCs of pharmaceutical distribution companies specifically. It also addresses an under-investigated area in the literature concerning the role of SCDO in promoting the adoption of SCD mitigation strategies.
This study investigates the antecedents of supply chain resilience of small and medium-sized enterprises (SMEs) and the effects of government assistance and disruption intensity in long-term disruptions.
This study collected data from 626 SMEs in Australia in 2022 and analysed data using partial least squares structural equation modelling.
The study empirically confirms that digital capabilities, prior experience in disruptions, supplier proximity and relationships are antecedents of supply chain resilience of SMEs, with supply chain robustness as a mediator. It further confirms that SMEs' access to government assistance positively moderates the relationship between digital capabilities and supply chain robustness. The disruption intensity moderates the relationships between supplier proximity and supply chain robustness with supply chain resilience. Severe disruptions weaken the effects of prior disruption experiences and supplier relationships on supply chain resilience.
The findings inform SME practitioners of the importance of building supply chain robustness, leveraging their prior experience, supplier proximity and relationships and capabilities and flexibility for dynamic supply chain structures when disruptions are intense.
The novelty of our study is the use of the Contingent Resource-Based View to understand the effects of firm and supply chain-level antecedents on supply chain robustness and resilience, considering the contextual contingencies of disruption intensity and government assistance. The focus on long-term disruptions extends the conventional supply chain resilience studies on supply and demand disruptions of small scale. We also explore the firm-level effects of government assistance, which extends the commonly tested economic-level effects. Furthermore, we investigate supply chain robustness and resilience as different but connected constructs, deviating from common approaches. The finding that the relationship between digital capabilities and supply chain robustness, not the relationship between digital capabilities and supply chain resilience, becomes stronger with higher access to government support shows the importance of this approach to investigating specific effects.
Natural calamities like earthquakes, floods and epidemics/pandemics like COVID-19 significantly disrupt almost all the supply networks, ranging from medicines to numerous daily/emergency use items. Supply Chain Resilience is one such option to overcome the impact of the disruption, which is achieved by developing supply chain factors with Artificial Intelligence (AI) and Big Data Analytics (BDA).
This research examines how organizations using AI and BDA can bring resilience to supply chains. To achieve the objective, the authors developed the methodology to gather useful information from the literature studied and developed the Total Interpretive Structural Modeling (TISM) by consulting 44 supply chain professionals. The authors developed a quantitative questionnaire to collect 229 responses and further test the model. With the analysis, a conceptual and comprehensive framework is developed.
A major finding, this research advocates that supply chain resilience is contingent upon utilizing supply chain analytics. An empirical study provides further evidence that the utilization of supply chain analytics has a positive and favorable effect on the flexibility of demand forecasting to inventory management, resulting in increased efficiency.
Few studies demonstrate the impact of advanced technology in building resilient supply chains by enhancing their factors. To the best of the authors' knowledge, no earlier researcher has attempted to infuse AI and BDA into supply chain factors to make them resilient.
The research paper’s purpose is to contribute to the literature by analysing the essential resources and processes required for successful commercialisation, the contemporary challenges and opportunities of artificial intelligence initiatives in Türkiye, and the diverse models and methods employed by these initiatives.
Within the scope of the research, interviews were conducted with 10 entrepreneurs who established artificial intelligence-oriented enterprises in technoparks in Istanbul and Antalya. All 10 interviews were analysed using the MAXQDA20 software tool. Structured qualitative content analysis was used for the data analysis procedure.
Based on the research, external factors have a significant impact on the future growth opportunities of the market. Expanding the client base, gaining international recognition, and securing financing are crucial for success. However, the findings reveal challenges in the relatively young local ecosystem. One major criticism is the lack of support in marketing and sales activities for refined products. To address this, providing financial incentives and knowledge transfer to those in need is vital.
Since the research was conducted only with entrepreneurs who established and successfully commercialised artificial intelligence-oriented enterprises, it is recommended that future studies be performed with a widespread sample group, considering this limited situation. Furthermore, to overcome survivorship bias, it is recommended that posterior studies include failed commercialisation attempts in AI ventures.
It can be argued that there is no deliberate approach or model for commercialization. Entrepreneurs often draw from their own prior experiences or observe industry trends. Given the limited financial resources available in the domestic market and the challenge of attracting foreign investors to Turkish brands, entrepreneurs tend to rely on internal approaches for commercialisation.
This research delves into the commercialisation prospects and obstacles encountered by AI start-ups in Türkiye. It comprises qualitative insights into business models, commercialisation approaches, opportunities, and challenges. The data were obtained from interviews with entrepreneurs operating in the industry.
The pervasive issue of employee exploitation has surfaced as a salient ethical quandary within the context of modern-day workplaces, thereby demanding expeditious and imperative deliberation and redressal. This research endeavor aims to meticulously investigate the ramifications of employee exploitation on the proclivity to partake in the act of cutting corners within the workplace. This analysis encompasses the sequential mediating variables of negative emotions, namely resentment, anger, and frustration, as well as moral disengagement.
A purposive sampling technique and self-administered questionnaires were utilized in this study of 132 SME sector personnel. The current study is time-lagged in nature and uses the Amos software, the data were analyzed using exploratory and confirmatory factor analyses, as well as structural equation modeling.
According to the results, employee exploitation has a strong positive impact on cutting corners. This effect is mediated progressively by negative emotions (resentment, anguish, frustration), as well as moral disengagement. According to the findings, organizations should prioritize addressing employee exploitation to build a healthy work environment that promotes employee well-being and encourages employee voice.
This study’s novelty comes from its analysis of the sequential mediation of negative emotions, as well as moral disengagement, in the relationship between employee exploitation and cutting corners. The study’s findings add to the body of literature concerning management development, conflict handling, and employees’ attitudes and behaviors by offering a thorough grasp of the detrimental effects of employee exploitation on cutting corners as well as useful recommendations for businesses looking to promote productive workplaces.
The survival of companies today hinges on their adaptability and flexibility, with digital transformation (DT) and organizational slack (OS) playing crucial roles. Despite their recognized importance, these factors are often studied separately. This study aims to explore how OS facilitates DT and evaluate their synergies and trade-offs to improve performance.
Using data from the European Manufacturing Survey, structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA), we investigate causal relationships and possible combinations between different dimensions of OS and DT that contribute to business performance.
We confirmed the positive effect of OS and DT on business performance, highlighting the importance of organizational over technological factors. While not definitively establishing OS as a precursor to DT, our findings underscore the need for human and operational slack to improve performance, especially in less technology-intensive contexts.
Our findings evidence that decision-makers should integrate OS with DT initiatives to improve the firm’s competitiveness. However, it is worth noting that while OS seems essential in low-tech shopfloors, its importance is lower in high-tech environments. Furthermore, within the possible combinations, managers should promote operational slack and digitalization, as it seems fundamental to improve business performance.
This article contributes to the management field in three ways. First, it clarifies controversies by providing evidence of the positive roles of DT and OS as drivers of competitiveness for manufacturing firms. Second, we verify that OS is not directly linked to DT, challenging existing assumptions. Third, it investigates the combinations of OS and DT that drive business performance improvement, emphasizing their synergies and trade-offs.
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