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This study examines the relationship between policyholders’ psychographic characteristics and demand decisions for life insurance products in Uganda.

The study is based on a cross-sectional survey. Using a purposive sampling method, 389 questionnaires were administered to life insurance policyholders in the four geographical regions of Uganda. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the primary data, specifically to test the relationships between the dependent and independent variables.

The findings indicate a positive and significant influence of psychographic characteristics on demand decisions for life insurance products. In addition, the analysis indicates that the two first-order constructs of psychographic characteristics, namely price consciousness and consumer innovativeness, are positive and significant predictors of demand decisions for life insurance products. In contrast, the third first-order construct religious salience, exhibits a negative and nonsignificant effect on demand decisions for life insurance products.

For insurance practitioners, to influence demand decisions, they should emphasize premium-related appeals in their marketing messages (price consciousness) ignore product decisions based on religious beliefs and norms (religious salience). They should also ensure that insurance products are highly trustable and experiential (consumer innovativeness). For insurance policymakers, it offers an in-depth understanding of customer psychographic characteristics, which can be used to identify exploitative information embedded in certain marketing campaigns targeting specific psychographic characteristics, for better regulation.

The study provides a basis for understanding lifestyle and personality characteristics (psychographics), which may influence demand decisions for life insurance products in a developing country like Uganda, where the insurance industry is at an early stage of development.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0440

Sustainable supply chain management (SSCM), driven by the downstream buyers' power, transfers sustainability responsibilities to the upstream supplier. In contrast to the heavily-focused buyers' perspective in the literature, the authors investigate how this buyer-driven SSCM influences suppliers' performance, using the measure of stock market reaction.

Grounded by the resource dependence theory (RDT), the authors empirically analyze the power effect on suppliers. Event study methodology and regression analysis are used, based on a sample of 1977 paired supplier observations from 1990 to 2016.

The result suggests that although a negative stock market reaction for suppliers in SSCM exists, the effect is less negative at a high level of buyer and supplier dependence. For the investigation of the “consolidated SSCM initiative,” where buyers acquire exogenous power by collaboratively managing SSCM with their peers, the authors uncover that the negative impact of this consolidated SSCM initiative can be mitigated by the high interdependence that generates relational norms in the dyads.

The authors focus on dyadic relationships. Future research can use the study's findings to study the SSCM diffusion to lower-tier suppliers.

This paper has good managerial implications for both suppliers and buyers. The authors propose dependence-based strategies for supplier managers to reduce uncertainty in SSCM. Moreover, buyer managers can use the study's findings to strengthen suppliers' commitment.

The novelty of examining the suppliers' perspective contributes to exploring the supply chain impact of SSCM. The authors extend RDT and show that high dependence is not necessarily detrimental to suppliers in this buyer-driven SSCM context. The interesting finding of interdependence in the context of the consolidated SSCM initiative brings new insights that relational norms constrain the leverage of power in the dyads and are beneficial to the power-disadvantageous suppliers.

This study examines the relationship between demand forecasting error and retail inventory management in an uncertain supplier yield context. Replenishment is segmented into off-season and peak-season, with the former characterized by longer lead times and higher supply uncertainty. In contrast, the latter incurs higher acquisition costs but ensures certain supply, with the retailer's purchase volume aligning with the acquired volume. Retailers can replenish in both phases, receiving goods before the sales season. This paper focuses on the impact of the retailer's demand forecasting bias on their sales period profits for both phases.

This study adopts a data-driven research approach by drawing inspiration from real data provided by a cooperating enterprise to address research problems. Mathematical modeling is employed to solve the problems, and the resulting optimal strategies are tested and validated in real-world scenarios. Furthermore, the applicability of the optimal strategies is enhanced by incorporating numerical simulations under other general distributions.

The study's findings reveal that a greater disparity between predicted and actual demand distributions can significantly reduce the profits that a retailer-supplier system can earn, with the optimal purchase volume also being affected. Moreover, the paper shows that the mean of the forecasting error has a more substantial impact on system revenue than the variance of the forecasting error. Specifically, the larger the absolute difference between the predicted and actual means, the lower the system revenue. As a result, managers should focus on improving the quality of demand forecasting, especially the accuracy of mean forecasting, when making replenishment decisions.

This study established a two-stage inventory optimization model that simultaneously considers random yield and demand forecast quality, and provides explicit expressions for optimal strategies under two specific demand distributions. Furthermore, the authors focused on how forecast error affects the optimal inventory strategy and obtained interesting properties of the optimal solution. In particular, the property that the optimal procurement quantity no longer changes with increasing forecast error under certain conditions is noteworthy, and has not been previously noted by scholars. Therefore, the study fills a gap in the literature.

This study established a two-stage inventory optimization model that simultaneously considers random yield and demand forecast quality, and provides explicit expressions for optimal strategies under two specific demand distributions. Furthermore, the authors focused on how forecast error affects the optimal inventory strategy and obtained interesting properties of the optimal solution. In particular, the property that the optimal procurement quantity no longer changes with increasing forecast error under certain conditions is noteworthy, and has not been previously noted by scholars. Therefore, the study fills a gap in the literature.

This paper empirically investigates the demand for pastured eggs in the United States and evaluates the welfare consequences of Japan's egg import tariff reductions for the US consumers.

Using household-level Nielsen Homescan panel data, a fixed-effects Heckman two-stage sample selection model is estimated.

The estimation results ascertain the importance of a set of household socioeconomic characteristics, which are found to influence both the purchase probabilities and the consumption amounts associated with pastured eggs. In addition, demand for pastured eggs is estimated to be inelastic, and pastured eggs are found to be a normal good, more specifically a luxury.

The dataset used in this study reflect purchases only for at-home consumption, lacking information on away-from-home purchases.

Building upon previous research, this study makes the following distinct contributions to the current literature. To the best of our knowledge, it constitutes the first study to empirically examine the demand for pastured eggs, using household-level panel data and an estimation model that not only allows for left-censoring but also controls for regional and time fixed effects. Second, the present study reflects a unique effort in analyzing the adverse welfare consequences of the increased egg prices in the United States brought by a reduction of Japanese import tariffs on US-supplied eggs, focusing specifically on pastured eggs.

Motivated by the wide application of procurement strategies in retailing, this paper aims to examine the effect of procurement strategies on decisions and profits and strategic inventory (SI) is considered.

The game-theoretic models are developed under a two-period fresh product supply chain (FSC), and consist of the mode of purchasing products only in the first period without SI (Scenario S), the mode of purchasing products in every period without SI (Scenario T) and the mode of purchasing products in every period with SI (Scenario TS).

Conducting the calculating and comparing, some major findings can be concluded. In general, two-period purchasing strategies (Scenarios T and TS) promote a higher freshness-keeping effort than the single buying strategy (Scenario S). Regarding the pricing strategy, SI and Scenario S can both contribute to obtaining a lower wholesale price, the retailer's pricing is relatively complicated and hinges on the consumer's sensitivity to freshness-keeping effort and the holding cost. Besides, comparing the sales quantity and the profit, the authors find that Scenario TS stimulates more demands and brings more profits for the manufacturer. However, Scenario TS is not the optimal selection for the reason that SI sometimes hurts the retailer and even the whole supply chain. Whereas, when the holding cost is in a certain range, Scenario TS will lead to a win-win situation.

The main findings of this study can give the enterprises some advice on the procurement strategies of fresh products and the decisions of pricing and the freshness-keeping effort.

Based on the stimulus-organism-response theory, this research constructs the influence of the stimulus factors of the live-streaming shopping environment on consumers' psychological situation. It then produces the research model of impulsive purchase intention.

In this study, the online questionnaire survey method was used to survey users who participated in live-streaming shopping, and a total of 335 valid questionnaires were collected. Then SPSS and SmartPLS were used for data empirical evaluation and hypotheses test.

Research results show that demand, convenience, interactivity, and playfulness are positively stimulating consumers' perceived enjoyment. And their perceived enjoyment directly drives their intention of impulsive purchase.

The choice of the live streaming platform, the design of the interactive interface, and the design of the shopping process are all factors that the streamer must carefully consider. The results of this study can be used as a reference for the development of live-streaming shopping and provide the industry with an understanding of the main factors that affect users' live streaming and impulsive purchases to plan an effective live streaming platform and content.

“E-commerce live streaming” is regarded as the latest trend of e-commerce, and impulse buying is regarded as a key factor in the success of transactions. This research has developed factors that influence impulsive purchases after watching live streaming based on the SOR theory.

This study aims to examine the impact of different levels of required book-tax conformity (BTC) on audit clients' demand for auditor-provided tax services (APTS). In addition, the authors also investigate the effects of the European Union (EU) Regulation (2014).

This study utilizes a sample of listed companies from 10 EU countries between 2010 and 2019. The final sample consists of 16,049 firm-year observations from 2,515 unique firms, and the authors use both probit and ordinary least square (OLS) regression models in this study.

The main finding of this paper is that companies listed in countries with a higher level of BTC are less likely to purchase tax services from incumbent auditors and pay fewer auditor-provided tax service fees. Results from further analyses confirm that firms substantially reduced their purchase of APTS after the EU Regulation (2014) was implemented, but these reduced purchases were found to be more pronounced for firms located in countries with low BTC.

This study advances the understanding of the determinants of APTS and the consequences of BTC. Specifically, the authors report that variation in a country-specific feature (i.e. BTC) also affects firms' decision to purchase APTS. Moreover, this paper provides some preliminary evidence of the new regulation and contributes to the literature on APTS regulation. The findings of this study have important policy implications for regulators and are also relevant for various capital market participants.

The purpose of this study was to explore the determinant factors of the adaptive clothing market for disabled customers and to identify the influential elements in the fashion industry, with the aim of establishing the influential factors that drive the adaptive apparel business in the local market. The study developed a path model of relationships incorporating the disabled consumer background, consumer purchase intention and demand and elements of the fashion industry. This model can be used as a reference for fashion practitioners.

A quantitative approach was adopted for this empirical study. A survey was designed to investigate the connections between the consumer-related and industry-related variables. A set of measurements was developed and validated for the survey. The data were collected from a sample of 175 local wheelchair users, with a response rate of approximately 6.6 per cent. The data were analysed using SmartPLS, and structural equation model analysis was applied to identify the relationships between the variables.

The results of this study demonstrated that consumer purchase intention for adaptive apparel was affected closely by environmental factors, and consumer demand was significantly related to industry aspects including the product complexity and the business operations along with all elements of the industrial practice. The findings also revealed that the disability level was related to the users' purchase intentions, but the financial capability of the disabled consumers did not affect the intention to purchase adaptive clothes products. These results could suggest that economic issues are not the consumer's prior concern when purchasing apparel, but rather the disability condition. Those who demand adaptive apparel require advanced performance levels of product design, technology application and service.

The study originated from the situation that the Hong Kong fashion market lacks an adaptive market specifically for the minority group of disabled consumers. Why such a niche market has not been developed is unclear to the practitioners. It is necessary to investigate from both consumer-related and industry-related factors. Specifically, the research explored the consumer background and industry elements to identify the factors that influence disabled consumers to purchase apparel, in order to inform fashion practitioners who are interested in the niche market of disabled consumers in Hong Kong. It is anticipated that the determinants of adaptive market development can be extended to wider areas of the Chinese or other Asian markets.

This study aims to identify supply chain (SC) management practices applied to purchasing capable of improving the resilience of the health-care SC and mitigating the effects of material and service disruption during pandemics.

The approach adopted is qualitative and is based on a systematic literature review from the ScienceDirect, Emerald, Wiley and Web of Science databases. After selecting 705 documents, filters are applied, and 52 articles present problems faced by purchasing the health-care SC during the coronavirus disease 2019 (COVID-19) pandemic.

This article suggests five propositions of resilient practices that can increase purchasing resilience in the face of pandemics such as COVID-19. The proposed practices are collaboration, flexibility, visibility, agility and information sharing, which suggest a sequence for the adoption of management practices based on the number of occurrences and importance found in the analysed studies.

This study does not find robust empirical evidence that could categorically state that the results can be replicated in organisations in general. Thus, as a continuation of research, more studies should use an empirical methodology and case analysis to organise different branches. As the human factor was decisive for the results observed in the literature, future research should dedicate part of the studies to the psychological area of professionals. Actions to combat the pandemic were implemented, impacting positively and negatively on the results obtained. Future research on combat actions could indicate which ones should be avoided.

As a result, disruptions are expected to be reduced, and consequently, the resilience of the SC will increase. Accordingly, purchasing processes and procedures can be redefined to positively influence the resilience of the health-care SC. Resilience is related to maintaining the flow of supply, as well as systems and actions aimed at mitigating the effects of disruptions in the hospital’s core business.

Health systems need to respond to society’s needs even in the face of global crises, such as the one faced during the COVID-19 pandemic. The overload in hospitals and the exponential demand for specific medicines and services in the fight against the crisis caused by the COVID-19 pandemic require enormous coordination in procurement by the purchasing sector. This planning aims to ensure that the care provided by health services maintains the flow of value that serves hospitalised patients.

This study introduces a new approach to the recurrent problem of disruption of the health-care SC during a pandemic using a combination of five important management practices. This proves useful for mitigating disruptions and their effects on the health-care SC.

The authors empirically examine purchasing strategy typologies based on strategic intent (i.e. competitive priorities) and practices used to achieve these priorities. The authors further investigate the implementation conditions of such strategies based on perceived uncertainty and strategic purchasing.

The authors utilize case study data from 11 international service and manufacturing firms with global supply chains. Each company was profiled based on the level of perceived environmental uncertainty, the characteristics of strategic purchasing, the use of relevant purchasing practices and its ability to create value through purchasing.

The study findings show that four purchasing strategy types exist: Purchasing Rationalization, Supply Base Optimization, Purchasing as a Service and World-Class Supply Base Management. Lower levels of perceived environmental uncertainty favor the adoption of rationalization strategies (i.e. Purchasing Rationalization and Supply Base Optimization), while increased uncertainty leads companies to switch to relationship-focused strategies (i.e. Purchasing as a Service and World-Class Supply Base Management). Further, that specific components of strategic purchasing (i.e. strategic planning, maturity, status and report level) enable the successful implementation of different strategy types.

This research contributes to the existing literature by outlining the different types of purchasing strategies and the external and internal factors that need to be considered to achieve strategic alignment and value creation in purchasing, and by classifying purchasing strategy types at the functional level based on empirical evidence.