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The purpose of this paper is to examine the demand curve for information on tourism destinations and accommodation. The current study compares the demand curves for this information to trends described by Chris Anderson as the “long tail”.

The current study examines the demand for information about accommodation establishments and destinations in Australia through the Australian Tourism Data Warehouse (ATDW). The study examines the demand for information received through the ATDW in 2009 for 5,600 Australian destinations and over 33,200 accommodation listings. Demand for information was measured by page impressions (PIs). Over 10 million PIs were received for destinations and more than 17 million PIs were received for accommodation listings, all of which were examined.

The current research shows that both accommodation and destination demand curves display the extended demand curve typical of the long tail phenomenon. The analysis also shows that demand curves within the aggregate demand curve also follow “long tail” demand curves. The study contributes to understanding of the demand curve for tourism information for Australian product using the ATDW.

The paper provides analysis of tourism information demand in the context of the “long tail” phenomenon.

The purpose of the study is to examine whether analyst coverage responds to changes in investor information demand for a firm and to test whether certain investor or firm characteristics moderate this association.

The authors model analyst activeness (AA) as a function of institutional investors' information demand, proxied by news readership on Bloomberg terminals and retail investors' information demand, proxied by the Google Search Volume Index (GSVI). Additionally, the authors take several steps to mitigate concerns about reverse causality that may confound the findings.

Results suggest that analysts respond to information demand shocks, but partially revert their coverage after the demand shock subsides. Furthermore, the results suggest that analysts cater their coverage more towards institutional investors than to retail investors. Evidence also suggests that analysts are more responsive to investors interested in firms with tech stock characteristics. Finally, the authors find evidence that specialist analysts respond more to institutional investors while generalist analysts respond more to retail investors.

The authors are the first to empirically examine the extent to which analysts cater to investor information demand. This is a vital topic to study because analysts are one of the primary sources of information for market participants. Understanding an analyst's motivation for providing information will help to facilitate market efficiency.

The rapid development of the Internet has led to an increasingly significant role for E-commerce business. This study examines how the green supply chain (GSC) operates on the E-commerce online channel (resell mode and agency mode) and the traditional offline channel with information sharing under demand uncertainty.

This study builds a multistage game model that considers the manufacturer selling green products through different channels. On the traditional offline channel, the competing retailers decide whether to share demand signals. Regarding the resale mode of E-commerce online channel, just E-tailer 1 determines whether to share information and decides the retail price. In the agency mode, the manufacturer decides the retail price directly, and E-tailer 2 sets the platform rate.

This study reveals that information accuracy is conducive to information value and profits on both channels. Interestingly, the platform fee rate in agency mode will inhibit the effect of a positive demand signal. Information sharing will cause double marginal effects, and price competition behavior will mitigate such effects. Additionally, when the platform fee rate is low, the manufacturer will select the E-commerce online channel for operation, but the retailers' profit is the highest in the traditional channel.

This research explores the interplay between different channel structures and information sharing in a GSC, considering price competition and demand uncertainty. Besides, we also considered what behaviors and factors will amplify or transfer the effect of double marginalization.

Different information sharing mechanisms and online platform information sharing to different charging models are compared and analyzed.

This paper uses the Stackelberg game model to study the demand information sharing and pricing decisions.

The results show that: (1) the retailer's pricing strategy is the highest when both of them obtain information, while the manufacturer's pricing strategy is affected by the related attributes of different products, such as the sensitivity of consumers to product prices; (2) in the online platform sales model, the demand information data sharing owned by the online platform can bring more expected profits to the whole supply chain and the members of the supply chain, and the higher the accuracy of the information, the higher the expected profit; (3) when the cost of obtaining demand information is zero, that is, the online platform shares the information data about market demand free of charge, the retailer and manufacturer tend to obtain information; (4) for the online platform, charging a certain fee can achieve higher expected profits than free sharing.

Based on the single platform online sales model, this paper uses the Stackelberg game model to study the demand information sharing and pricing decision of a manufacturer and a retailer selling products through the same online platform.

Couriers are in an unequal relationship with on-demand logistic platforms with regards to order assignment and delivery-related information acquisition, which leads to high courier turnover rates. Based on social cognitive theory and justice theory, this research investigates the impact of order assignment and delivery-related information disclosure strategy on couriers' perceived justice and continuous participation intention and presents managerial suggestions to on-demand logistic platforms to lower the courier turnover rate.

Taking Chinese couriers as experimental subjects, this study conducts experiments by constructing an order receiving scene of order assignment strategy (performance-priority vs distance-priority) and delivery-related information disclosure strategy (detailed-information vs brief-information) and analyzes the results of 452 valid respondents.

The results indicate that the interaction between order assignment and delivery-related information disclosure strategy in on-demand logistics significantly affects couriers’ continuous participation intention, specifically under performance-priority order assignment and detailed-information (vs brief-information) disclosure strategy. Informational justice and distribution justice play mediating roles, and work experience and proactive personality moderate the relationship interactions.

The research helps us to understand the order-receiving justice demand and delivery-related information demand of couriers in on-demand logistics platforms and sheds light on cutting down turnover rates through different strategies designs and justice environment construction.

This research integrates social cognitive theory into on-demand logistics and combines with justice theory to fill platform strategies, couriers’ justice perception and characteristics, as well as behavior into “triadic reciprocal causation.” Meanwhile, it investigates different impacts and interactive relationships of order assignment and delivery-related information disclosure strategy, expands strategies from the impact of operational efficiency to the impact of couriers’ participation and extends the literature of justice perception and individual characteristics in on-demand logistics.

The development of information technology has made it possible for companies to get access to information about their customers ' future demand. This paper outlines various approaches to utilize this kind of visibility when managing inventories of end products on an operative level. The purpose is to explain the consequences, for capital tied up in inventory, of sharing four different types of planning information (point-of-sales data, customer forecasts, stock-on-hand data, planned orders) when using re-order point (R,Q) inventory control methods in a distribution network.

A simulation study based on randomly generated demand data with a compound Poisson type of distribution is conducted.

The results show that the value of information sharing in operative inventory control varies widely depending on the type of information shared, and depending on whether the demand is stationary or not. Significantly higher value is achieved if the most appropriate types of information sharing are used, while other types of information sharing rather contribute to decreased value. Sharing stock-on-hand information is valuable with stationary demand. Customer forecast and planned order information are valuable with non-stationary demand. The value of information sharing increases when having fewer customers, and when the order quantities are large. Sharing point-of-sales data is not valuable, regardless of the demand type.

The use of simulation methodology is a limitation, because the study has to be limited to a specific model design, and because it is not based on primary empirical data. The study is especially limited to dyadic relationships in supply chains, and to distribution networks with a rather limited number of customers.

Guidance is given about what type of information should be appropriate to share when different types of demand patterns and distribution networks, and how order batch sizes and lead times affect the value of information sharing when using re-order point (R,Q) methods.

Very limited research providing specific assessments of potential inventory control consequences when sharing planning information in various contexts has been found in the literature. The findings and conclusions also question some previous research on information sharing.

This paper aims to study the node modeling, multi-agent architecture and addressing method for the material conscious information network (MCIN), which is a large-scaled, open-styled, self-organized and ecological intelligent network of supply–demand relationships.

This study models the MCIN by node model definition, multi-agent architecture design and addressing method presentation.

The prototype of novel E-commerce platform based on the MCIN shows the effectiveness and soundness of the MCIN modeling. By comparing to current internet, the authors also find that the MCIN has the advantages of socialization, information integration, collective intelligence, traceability, high robustness, unification of producing and consuming, high scalability and decentralization.

Leveraging the dimensions of structure, character, knowledge and experience, a modeling approach of the basic information can fit all kinds of the MCIN nodes. With the double chain structure for both basic and supply–demand information, the MCIN nodes can be modeled comprehensively. The anima-desire-intention-based multi-agent architecture makes the federated agents of the MCIN nodes self-organized and intelligent. The MCIN nodes can be efficiently addressed by the supply–demand-oriented method. However, the implementation of the MCIN is still in process.

This paper lays the theoretical foundation for the future networked system of supply–demand relationship and the novel E-commerce platform.

The authors believe that the MCIN, first proposed in this paper, is a transformational innovation which facilitates the infrastructure of the future networked system of supply–demand relationship.

This paper aims to examine the effect of inventory information sharing on inventory efficiency and its intervening effect of information technology (IT) capability in manufacturing firms.

Stratified random sampling and filter questions selected targeted respondents, and an online survey collected 124 completed questionnaires from Malaysian manufacturing firms. partial least squares structural equation modeling (PLS-SEM) examined the structural model and hypothesis statement. An analysis of importance-performance map analysis (IPMA) test identified the relative importance drivers of inventory efficiency.

The findings showed that enhanced IT capabilities in manufacturing firms mediate a positive relationship between inventory sharing and inventory efficiency.

This study portrays the relationship between inventory level, demand and information sharing. The research was carried out only within Malaysian manufacturing firms.

These findings will enable the management of manufacturing firms to design and visualise their inventory levels and share best practices across supply chain networks to achieve effective and optimised inventory planning.

This study illustrates an intervention model that offers a direct and indirect impact of IT capabilities that allow scholars to close inventories productivity gaps in research.

This paper extends the limited literature on the sharing of inventory information and inventory productivity, notably from a strategic management perspective. The findings help scholars clearly understand the information systems capability and its mediating impact on information sharing and inventory efficiency’s relationship in the manufacturing sector. Moreover, demand information sharing affected the dynamic supply chain.

This paper aims to explore the influence of specific characteristics of the public sector in developing countries (i.e. a low‐institutional capacity, a limited involvement of stakeholders, and high levels of corruption and informality), and of reforms of this sector, on public sector performance measurement (PSPM).

Based on a review of prior literature, the paper develops understanding of the demand for and supply of performance information in developing countries, and of changes in this area.

The paper argues that public sector organisations in developing countries are likely to face an unbalanced position, i.e. disequilibrium between the demand for and supply of performance information. More precisely, the public sector reforms – which are partly stimulated by a growing involvement of some stakeholders – lead to an increasing demand for performance information but, because of the low‐institutional capacity and the high level of corruption, this increasing demand is not always followed by a sufficient supply of performance information. This leads to an “unsatisfied demand” position.

The paper concludes with an overview of issues related to PSPM in a developing country context that require further investigation.

The arguments presented in this paper are summarised in an overview of factors that influence the demand for and supply of performance information in the public sector in developing countries. This overview might be helpful to those who are involved in the design of performance measurement systems in these countries.

So far, relatively little is known about PSPM in a developing country context. This paper is an attempt to fill this gap.

The purpose of this paper is to promote decision-making structures between the customer and the supplier in a highly uncertain environment. This phenomenon of demand-supply chain synchronisation includes sharing of high-quality and timely demand and supply information in order to improve the quality and speed of decision-making.

The study was carried out as an abductive case study, which started from empirical observations that did not match the prior theoretical framework. Through abductive reasoning and empirical experiments, the prior framework was extended to a new synchronisation model and tools that better accommodate the observed need.

A new co-innovation toolbox was developed to create common understanding of demand-supply chain synchronisation between the customer and the supplier. The toolbox includes Demand Visibility Point-Demand Penetration Point, Supply Visibility Point–Supply Penetration Point and Integrative Synchronisation tools.

The study extends the current models and tools of demand-supply chain synchronisation. With the new toolbox, the development needs of decision-making structures can be identified more comprehensively than with the current tools.

The developed visual toolbox helps partners create a common understanding of problems and development possibilities in demand-supply chain synchronisation in a highly uncertain environment. Common understanding is a starting point for changing decision-making structures to improve the overall performance of a demand-supply chain.

The new toolbox is both more comprehensive and more detailed than the previous tools.