Search results

Supply chain practitioners have made great strides in forming collaborative partnerships, yet the end consumer is often left out of these plans. Being an important member of the supply chain, we propose that supply chains need to get closer to the end consumer ‐ forming collaborative relationships that center around demand planning. Developing subscription relationships with end consumers will lead to increased planning time, which will result in dramatic cost reductions and superior consumer value and satisfaction through lower costs, increased convenience, and improved availability of supply. Being a new and unique strategy, not all consumers will adopt subscription supply chains. However, we argue that some consumer segments will receive tremendous value and satisfaction purchasing certain types of products and services through subscriptions. Tremendous opportunities await those supply chains who target the right consumers, marketing the right products and services through a subscription supply chain.

The purpose of this paper is to investigate the retailer’s strategy of information sharing in a green supply chain with promotional effort, and the impact of information sharing on the decisions and profits of the manufacturer and the retailer.

The developed models aim to maximize the profits of the manufacturer, the retailer and the green supply chain system. The game theory is used to obtain the equilibrium solutions of both the manufacturer and the retailer. A two-part compensation (TPC) contract is designed to motivate the retailer to share information with the retailer. Numerical examples are used to show the impact of parameters on decisions by Matlab 2014.

The results show that the green degree increases while the promotional effort level decreases when the manufacturer receives the larger demand information from the retailer; information sharing leads to a profit increase to the manufacturer and a profit loss to the retailer, but can increase the profit of supply chain under a certain condition; information sharing reduces the expected consumer surplus. The TPC contract designed in this paper can not only motivate the retailer to share information but also increases the consumer surplus.

The study has been done in a monopoly environment where only a retailer can forecast demand information. It is an interesting direction of future research when considering there are more retailers who can forecast such information in a supply chain.

There exist two main aspects that are different from the existing literature. The stochastic demand function related to the retail price, the green degree and the promotional effort have never appeared in previous literature. This paper considers a green product supply chain with a manufacturer who produces green products and a retailer who has an information advantage because of her promotional effort; this paper investigates the impact of information sharing on the consumer surplus and designs a contract to coordinate the green supply chain.

General economic theories of consumer demand work well in describing market behaviour with respect to most purchases and the explanation of consumer choice between competing commodities is clearly acceptable for the great majority of scarce goods. However, these theories do not easily accommodate the many non‐economic factors associated with preference formation and with the shaping of consumer attitudes and values. They also pay little or no attention to the dynamic process of choice, purchasing and consumption; in effect, they treat purchasing, consumption and satisfaction as synonyms.

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

The authors hope to filter valuable information from online reviews, obtain objective and accurate information about the demands of auto consumers and help auto companies develop more reasonable production and marketing strategies for healthy and sustainable development. This paper aims to discuss the aforementioned objectives.

The authors collected review data from online automotive forums and generated a corpus after pre-processing. Then, the authors extracted consumer demands and topics using the LDA model. Finally, the authors used a trained Word2vec tool to extend the consumer demand topics.

Different types of vehicle consumers have the same demands, such as “Space,” “Power Performance,” and “Brand Comparison,” and distinct demands, such as “Appearance,” “Safety,” “Service,” and “New Energy Features”; consumers who buy new energy vehicles are still accustomed to comparing with the brands or models of fuel vehicles; new energy vehicles consumers pay more attention to services and service quality during the purchasing and using process.

The development time of new energy vehicles is relatively short, with some models being available for only one year or even six months. The smaller amount of available data may impact the applicability of topic models. The sample size, especially for new energy vehicles, needs to be increased to improve the general applicability of topic models further.

First, this measure helps online review websites improve their existing review publication mechanisms, enhance the overall quality of online review content, increase user traffic and promote the healthy development of online review websites. Second, this allows for timely adjustments in future product production and sales plans and further enhances automotive companies' ability to leverage online reviews for Internet marketing.

The authors have improved the accuracy and stability of the fused topic model, providing a scientific and efficient research tool for multi-dimensional topic mining of online reviews. With the help of research results, consumers can more easily understand the discussion topics and thus filter out valuable reference information. As a result, automotive companies may gain information about consumer demands and product quality feedback and thus quickly adjust production and marketing strategies to increase sales and market share.

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.

The purpose of this paper is twofold. First, the study examines the prolonged effect of policy-related economic uncertainty on hotel operating performance, particularly the room demand (occupancy). Second, the study attempts to explain why occupancy drops when the perceived economic uncertainty is high by studying the mediating effect of consumer sentiment in the relationship between economic policy uncertainty and hotel demand.

This quantitative study uses secondary data – US economic policy uncertainty (EPU) index, University of Michigan's index of consumer sentiment (ICS), and property-level hotel operating data from three states of the US – California, Florida and New York. Data were analyzed using random effect regression and structural equation modeling. Robustness tests were conducted to enhance the reliability of the research findings.

Random-effects regression analysis reveals that policy-related economic uncertainty has a negative and lead-lag effect on hotel occupancy, average daily rate and revenue per available room (RevPAR). Structural equation modeling results show that the relationship between economic policy uncertainty and hotel occupancy is significantly mediated by consumer sentiment. Robustness test results support the findings from the main analysis.

This study offers valuable implications for the hotel professionals in regard to anticipating the economic impact of policy-related uncertainty on hotel industry and understanding how consumer sentiment affects demand at such crises times. Moreover, the study suggests potential course of actions to deal with declining room demand at times of uncertainty.

This empirical study explores how economic policy uncertainty affects hotel performance at the property level and explains the mediating effect of consumer sentiment on hotel room demand. The study provides a first-hand evidence of how consumer sentiment relates to the perception of economic uncertainty and leads to decline in consumer demand. In that regard, findings of the study have valuable implications for hospitality industry practitioners and relevant policymakers.

Technological development has not only helped in effective integration of renewable sources but also made it possible for consumers to participate in system operation. Different market players are coming up in the electricity market, microgrid being one of them. Thus, this paper aims to investigate consumers’ role in the dispatch of a microgrid system that has a hybrid market structure under varied system conditions.

The mathematical model developed has been solved by the CONOPT solver in the GAMS optimization tool. GAMS-MATLAB interfacing is done to obtain solutions.

The problem formulated shows the effect of consumers in dispatch and overall operational cost. Consumers’ participation has been proposed through a quadratic cost function. The system operation under pool and bilateral contracts has been investigated. It shows that proper incentives to the consumers can help in reduction and effective management of the demand, carbon emission and overall system operational cost.

This paper considers the hybrid market structure to find the load dispatch in a microgrid system. The participation of consumers in the microgrid system has been implemented considering variations in wind power, solar power and load. The power exchange between the grid and microgrid system has been modeled showing the contribution of the consumers in system operation.

Information sharing is one of essential collaboration methods for building effective system-level disruption responses and communication for supply chain resilience. However, supply chain members are often reluctant to share the members' business information for fear of losing competitiveness. To facilitate the cooperation among these members, the supply chain members' should be made aware of the value of information. As a result, the purpose of this paper is to quantify the benefit of information sharing and evaluate its magnitude under various factors.

In this paper, information sharing is measured in a two-stage supply chain containing a manufacturer and a retailer. A demand function is constructed as a linear combination of a first-order autoregressive [AR(1)] process, the retail and reference prices. The values of information sharing are quantified for four scenarios: (1) no information sharing, (2) full information sharing, (3) limited information sharing and (4) partial information sharing. Based on the four scenarios, the conditions for valuable information sharing are determined. In addition, the impact of several demand parameters on the usefulness of information sharing is analyzed.

When the demand function is a pure AR(1) process (i.e. there is no impact from the retail and reference prices), information sharing is always valuable regardless of the autoregressive coefficient. Under the influence of the retail price and consumer behavior via the reference price, information sharing is not always beneficial. The boundaries for useful information sharing are analytically constructed. In addition to full information sharing, this study also quantifies the value of information under a partial sharing scheme. The results indicate that the information is more valuable as long as the information is inducible.

This study highlights several specific conditions for a beneficial information sharing agreement in consideration of consumer behaviors. These conditions enable supply chain members to design a sustainable partnership.