Search results

The development of the digital age has made data and information more transparent, enhancing the strategic perspectives of both buyers (strategic waiting) and sellers (price fluctuations) in their decision-making. This research investigates the optimal dynamic pricing strategy of the content product developer in relation to their consideration of consumer fairness concerns to elucidate the impact of consumer fairness concerns on the dynamic pricing strategy of the developer.

This paper assumes that monopolistic content developers implement a dynamic pricing strategy for the content product. Through constructing a two-period dynamic pricing game model, this research investigates the optimal decisions of the content developer, contingent upon their consideration or disregard of consumer fairness concerns. In the extension section, the authors additionally account for the influence of myopic consumers on these optimal decisions.

Our findings reveal that the degree of consumer fairness concerns significantly influences the developer’s optimal dynamic pricing decision. When a developer offers content products with lower depth, there is a propensity for the developer to refrain from incorporating consumer fairness concerns into a dynamic pricing strategy. Conversely, in cases where the developer offers a high-depth content product, consumer fairness concerns benefit the developer. Furthermore, our analysis reveals a consistent benefit for the developer from the inclusion of myopic consumers.

Few studies have delved into the conjoined influence of consumer fairness concerns and strategic behavior on dynamic pricing strategy. Our findings indicate that consumer fairness concerns can enhance the efficiency of the value chain for content products under specific conditions. This paper not only enriches the existing literature on dynamic pricing by incorporating consumer fairness concerns theoretically but also offers practical insights. The outcomes of this research can guide content product developers in devising optimal dynamic pricing strategies.

The construction industries at present are focusing on designing sustainable concrete with less carbon footprint. Considering this aspect, a Fibre-Reinforced Geopolymer Concrete (FGC) was developed with 8 and 10 molarities (M). At elevated temperatures, concrete experiences deterioration of its mechanical properties which is in some cases associated with spalling, leading to the building collapse.

In this study, six geopolymer-based mix proportions are prepared with crimped steel fibre (SF), polypropylene fibre (PF), basalt fibre (BF), a hybrid mixture consisting of (SF + PF), a hybrid mixture with (SF + BF), and a reference specimen (without fibres). After temperature exposure, ultrasonic pulse velocity, physical characteristics of damaged concrete, loss of compressive strength (CS), split tensile strength (TS), and flexural strength (FS) of concrete are assessed. A polynomial relationship is developed between residual strength properties of concrete, and it showed a good agreement.

The test results concluded that concrete with BF showed a lower loss in CS after 925 °C (i.e. 60 min of heating) temperature exposure. In the case of TS, and FS, the concrete with SF had lesser loss in strength. After 986 °C and 1029 °C exposure, concrete with the hybrid combination (SF + BF) showed lower strength deterioration in CS, TS, and FS as compared to concrete with PF and SF + PF. The rate of reduction in strength is similar to that of GC-BF in CS, GC-SF in TS and FS.

Performance evaluation under fire exposure is necessary for FGC. In this study, we provided the mechanical behaviour and physical properties of SF, PF, and BF-based geopolymer concrete exposed to high temperatures, which were evaluated according to ISO standards. In addition, micro-structural behaviour and linear polynomials are observed.

The purpose of this study is to investigate the influencing mechanism of consumers' continuous purchase intention toward the subscriber-based knowledge payment platforms (SBKPPs).

This study obtained 226 valid samples through questionnaire surveys and used partial least square structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) methods to elucidate the complex causal patterns of consumers' continuous purchase intention toward the SBKPPs.

The findings revealed that perceived utilitarian value, perceived hedonic value and perceived social value directly affected consumers' continuous purchase intention, while content quality and service quality indirectly affected consumers' continuous purchase intention. In addition, this study also demonstrated that all factors must be combined to play a role, and there exist four configurations resulting in consumers' continuous purchase intention toward the SBKPPs.

The results can help researchers and practitioners better understand the causal patterns of consumers' continuous purchase intention toward the SBKPPs.

This study contributes to the knowledge payment literature by investigating consumers' continuous purchase intention toward the SBKPPs. This study also provides practical enlightenment for the SBKPPs' marketing.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

Despite efforts to reduce environmental pollution and wasteful fossil fuel use, electric vehicles (EVs) are still rare on the road. Why is it so challenging to get widespread EV adoption? One significant factor on which it heavily depends is one's awareness and understanding of EVs. However, due to an absolute lack of knowledge on the part of the populace, this factor becomes a huge impediment to the uptake of EVs. A systematic review of the electronic database Scopus for the years 2003–2022 was carried out on ‘EV awareness and adoption of EV’ while considering the ‘Preferred Reporting Items for Systematic Reviews and Meta-analysis’ (PRISMA) standards. A three-step identification process resulted in the ultimate detection of 41 papers, which were then thoroughly examined. A conceptual framework that encompasses the three key awareness aspects that influence EV adoption is developed. To encourage greater uniformity among EV researchers, this study's conclusions serve as a foundation for operationalising upcoming research efforts within a predetermined framework. The authors must therefore be optimistic that lingering technological, legislative, cultural, behavioural and business-model barriers may be overcome over time through widespread dissemination of knowledge and awareness related to EVs, making it possible for everyone to switch to greener, more economical and more efficient transportation solutions.

This paper aims to examine the existing literature on firms’ power through the lens of the supply chain and highlights some gaps that could be covered by future research.

This study uses a systematic framework-based review combining the insights of the antecedents, decisions and outcomes (ADO) and theories, contexts and methods (TCM) frameworks. The review was carried out using a sample of 108 articles published between 1984 and 2022 in 25 prestigious journals.

The ADO framework maps out the state of the art of the antecedents of power (i.e. sources and types of firm power), the decision to use power and the effect that exercising power over other firms may have on firm performance and the quality of inter-firm relationships. In addition, this framework highlights factors that mediate or moderate the decision to exercise power and the factors that mediate or moderate the outcomes of exercising power or power asymmetry. The TCM framework provides insights into the theories, contexts (i.e. countries, industries, level of analysis and sources of data) and methods used by the existing literature. The content analysis using the aforementioned frameworks provides the basis to elaborate propositions for future research on power in the supply chain from the perspective of gender differences.

This systematic literature review offers a comprehensive guide for researchers to understand the antecedents, decisions and outcomes of firm power in the supply chain, as well as the TCM used in the literature. The content analysis using frameworks provides a road map to investigate the proposed factors that might moderate the decision to exercise power and the outcome of exercising power or power asymmetry from the perspective of gender differences. In addition, based on content analysis, the authors make propositions about TCM that could be applied in future research.

From a practical perspective, this systematic literature review may help managers to better understand the sources and consequences of their firm’s power. This would allow managers to make better decisions when negotiating with their supply chain parties, which could potentially lead to better performance for their firms and the whole supply chain.

To the best of the authors’ knowledge, this study is the first to conduct a comprehensive systematic literature review of the different dimensions of firms’ power in the supply chain.

Our prior work has identified a trade-off that new entrants face in obtaining favorable market reception, whereby initial entrants suffer from a deficit of legitimacy whereas later entrants suffer from a deficit of authenticity. This research has also proposed that a single mechanism is responsible for this trade-off: the tendency for customers and other stakeholders to assess the entrant's claim to originality based on the visible work that it has done to legitimate the new product or organizational form. This chapter extends and deepens our understanding of such “legitimation work” by showing how it can illuminate cases that seem in the first instance to defy this trade-off. In particular, we focus on two “off-diagonal” cases: (a) when, as in the case of “patent trolls” and fraudulent innovators, early entrants are viewed as inauthentic despite having a credible claim to originality; (b) when late entrants, as in the case of Dell Computers, mechanical watches and baseball ballparks, are viewed as authentic despite obviously not being the originators. We clarify how each off-diagonal case represents an ‘exception that proves the rule’ whereby audiences attribute authenticity on the basis of legitimation work rather than on the order of entry per se. The last case also leads to an opportunity to clarify why “cultural appropriation” can sometimes project authenticity and sometimes inauthenticity, why audiences bother to make inferences about a producer's authenticity on the basis of visible legitimation work, and why legitimacy is a universal goal of early movers whereas authenticity varies in its importance.

This paper aims to examine the impact of six possible foreign direct investment (FDI) spillover channels on the total factor productivity (TFP) of Chinese agricultural enterprises and investigate the moderating role of absorptive capacity (technological acumen) on TFP spillover effects.

Based on data from 118 agricultural and related Chinese industries, the authors employ a multithreshold regression model to empirically analyze the impact of FDI on the TFP of agricultural enterprises and the threshold effect of absorptive capacity. To overcome potential endogeneity problems, the authors select the FDI stock of corresponding USA industries and the industrial access policy index as instrumental variables and re-estimate the model.

The results suggest foreign-invested agricultural enterprises are more likely to benefit from FDI, while the “aggregate” FDI spillover effect is negative for domestic agricultural enterprises. However, once threshold effects are introduced, the authors find firms “close to” (“far from”) the technological frontier experience statistically significant positive (negative) spillover effects. Similar results are obtained for virtually all FDI spillover channels for firms in both upstream and downstream industries. FDI spillovers, when they occur, can be a two-edged sword – benefiting some firms at the expense of others.

The authors introduce six FDI spillover channels to examine the impact of FDI on the productivity of foreign-invested and domestic agricultural enterprises. Moreover, the authors analyze the threshold effect of firms' absorptive capacity. These findings can help formulate foreign investment introduction policies based on the characteristics of agricultural enterprises with different ownership structures. These results are also beneficial for agricultural enterprises to better exploit FDI spillover effects and improve their productivity.

The crowdfunding concept and activities have recently been the focus of attention of many researchers and practitioners over different business contexts. However, there is a dearth of literature considering the main aspects of e-equity crowdfunding activities and their impact on the innovation performance for entrepreneurial business. Therefore, this study aims to explore how entrepreneurs' engagement in e-crowdfunding activities could enhance both knowledge acquisition and innovation performance.

The conceptual model will be proposed based on three main theoretical perspectives: relationship marketing orientation (RMO); Kirzner's alertness theory; and the DeLone and McLean model of information systems. The data of the current study were collected using an online questionnaire from a sample of 500 entrepreneurs who have actively engaged in e-crowdfunding in Saudi Arabia.

The statistical results of structural equation modelling (SEM) approved the impacting role of RMO, entrepreneurial alertness, system quality and service quality on the entrepreneurs' engagement in e-equity crowdfunding, which in turn, predicts both knowledge acquisition and innovation performance.

There are several limitations which could be addressed in future studies, for example, this study has only considered one form of crowdfunding (equity based crowdfunding) and due to its nature these findings would not be easily generalized to other kinds of crowdfunding (i.e. donation-based crowdfunding; rewards-based crowdfunding; and debt-based crowdfunding). Future studies could consider these kinds of crowdfunding activities.

This study has contributed to the understanding of e-equity crowdfunding in several aspects. For example, this study presents results that assist both researchers and practitioners in the Middle East and Saudi Arabia to develop an in-depth knowledge of e-equity crowdfunding by considering new dimensions such as RMO and information system success factors.

This paper aims to investigate the performance of two novel numerical methods, the face-based smoothed finite element method (FS-FEM) and the edge-based smoothed finite element method (ES-FEM), which employ linear tetrahedral elements, for the purpose of strength assessment of a high-speed train hollow axle.

The calculation of stress for the wheelset, comprising an axle and two wheels, is facilitated through the application of the European axle strength design standard. This standard assists in the implementation of loading and boundary conditions and is exemplified by the typical CRH2 high-speed train wheelset. To evaluate the performance of these two methods, a hollow cylinder cantilever beam is first used as a benchmark to compare the present methods with other existing methods. Then, the strength analysis of a real wheelset model with a hollow axle is performed using different numerical methods.

The results of deflection and stress show that FS-FEM and ES-FEM offer higher accuracy and better convergence than FEM using linear tetrahedral elements. ES-FEM exhibits a superior performance to that of FS-FEM using linear tetrahedral elements, showing accuracy and convergence close to FEM using hexahedral elements.

This study channels the novel methods (FS-FEM and ES-FEM) in the static stress analysis of a railway wheelset. Based on the careful testing of FS-FEM and ES-FEM, both methods hold promise as more efficient tools for the strength analysis of complex railway structures.