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The diffusion of technologies from other sectors, and innovations in kitchen equipment, fueled structural changes within the foodservice industry. However, this change comes at a price of disrupting the critical step of assessing the demand forecast accuracy. This study aims to explore a surprisingly unique and elevated complexity when assessing the critically important demand forecast accuracy.

The paper develops a mathematical model to describe and explore the nature of the problem in structural biased demand forecast accuracy assessment. It then uses numerical simulation to construct a market example to gain better insights on the bias characteristics. Finally, the forecast accuracy measurement’s inherent bias is contrasted with that of other typical hospitality forecasting setups.

This paper outlines the theoretical underpinnings of how demand forecasts in the central kitchen setup are dynamic and thus produce a structural bias. More specifically, this paper discovers how, in this context of orders from a central location, the forecasts set the capacity constraints, and, consequently, generate a considerably more biased forecast accuracy measure. Relying on such forecast accuracy measures can lead to serious negative business outcomes.

To the best of the author’s knowledge, this study is the first to show that in the unique new technology enabled environment of central kitchen operation, where daily dish demand forecasts set the daily constrained capacity levels, the accuracy measure is severely biased, and consequently accuracy is likely to deteriorate, which in turn, could lead to suboptimal decisions. The major theoretical contribution of this study is a novel analytical model which explains and describes the bias in the accuracy measurement.

技术从其他行业的传播以及厨房设备的创新推动了餐饮业内的结构变化。然而, 这种变化直接影响了评估需求预测准确性。本研究探讨了在餐饮业结构改变后，评估至关重要的需求预测准确性时所面临的令人独特和复杂性。

本文自研了一个数学模型来描述和探讨评估需求预测准确性中的结构性偏差的本质。然后, 使用数值模拟构建一个市场示例, 以更好地了解上述偏差的特征。最后, 将这种预测准确性评估的系统性偏差与其他传统的餐饮业需求预测情境进行对比。

本文概述了中央厨房运营中需求预测是动态的, 因此产生了结构性偏差的理论基础。更具体地说, 在使用中央厨房并集中订单的情境下, 本文发现需求预测直接设定了容量限制, 因此产生了在需求预测准确度衡量中的结构性偏差。依赖这样的预测准确性度量可能产生严重的负面商业结果。

这项研究首次表明, 在中央厨房运营的独特的新环境中, 由于新的设定即每日菜品需求预测直接决定每日容量水平, 需求预测准确度衡量标准有着严重偏差, 长期来讲准确性可能下降, 从而导致次优的商业决策。本研究的主要理论贡献是提供一个餐饮企业在新运营环境中解释和描述需求预测准确度中结构性偏差的全新分析模型。

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.

This paper aims to study the preferences of the supply chain (SC) members on various power structures under demand information asymmetry considering competing retailers.

A two-level SC with one manufacturer and two retailers is designed. The retailers are in Bertrand competition. The manufacturer who holds the confidential demand information chooses the appropriate information sharing (IS) format. Three IS formats are provided, i.e. no IS (the manufacturer never shares with the retailers), partial IS (the manufacturer shares with one retailer), full IS (the manufacturer shares with all retailers). In addition, the authors model two power structures based on the decision sequences in the SC, i.e. retailers or manufacturer-dominant SC. The authors characterize the equilibrium solutions and payoffs and then investigate the members’ preferences for IS formats.

It is shown that in retailers (manufacturer)-dominant SC, the retailers prefer full (no) IS, but the manufacturer prefers no (full) IS. Moreover, the authors analyze the members’ preferences on power structures under demand information asymmetry, which has a relationship with the degrees of demand uncertainty and competition intensity.

The analysis regarding the preferences of the SC members on power structure under demand information asymmetry provides valuable managerial insights to enhance cooperation and achieve a win-win result.

Building on the premise that the CEO position is complex and challenging, and drawing on research on upper echelons, executive job demands and emotions, this study explores how chief executive officers' (CEOs’) perceptions of job-associated difficulty can influence negative emotional displays and subsequently hamper firm innovation. Additionally, the authors explore how CEOs with higher levels of emotional intelligence might mitigate the influence of job demands on negative emotional displays.

The authors conducted a two-stage survey with a sample of CEOs and top management team members from 120 small- and medium-sized firms operating in multiple industries in Colombia.

The authors found that CEOs' perceptions of job demands are positively associated with CEOs' displays of negative emotions, which in turn are negatively associated with firm innovation. The authors also find that two dimensions of emotional intelligence (self-appraisal and regulation) weaken the influence of CEO perceptions of job demands on CEO negative emotional displays.

The authors advance a novel perspective on the challenges of leading organizations by explaining the emotional implications of the CEO position, underscoring their repercussions for important organizational outcomes such as innovation and suggesting potential ways CEOs can handle the emotional consequences of their position.

The empirical estimates for the money demand function reported here are based on quarterly time series for Saudi Arabia for the period 1962/I to 1981/IV. The money demand function estimated in this article is novel in that it takes into account the potential effect of external monetary and financial factors on domestic money de‐mand in the open economy of Saudi Arabia. The empirical results show that these external factors (foreign interest rates and exchange rates) do play an important role in the Saudi money demand function. Hence, the Saudi monetary authorities should not ignore the response of domestic money demand to these external factors in formulating their stabilisation policies. The empirical evidence also indicates that the inflationary expectations and permanent real income variables exert significant influences on money demand, with the latter variable exhibiting a unitary long‐run elasticity. Finally, the estimated money demand equation is found to be structurally stable over time.

The unacknowledged and obscure mechanisms which “inflate” demand for health care provisions, thereby exacerbating the persistent gap between demand and the resources available to meet it, are considered. It is suggested that the structural scrutiny of emergent medical research ‐ alongside health promotion measures ‐ could be used as a means to moderate health care demand. It is argued that anti‐utilitarian objectives to this approach may be equally levelled at laissez‐faire justifications for unfettered research.

Many lodging operators in the USA might intuitively, or through long experience, be aware of the more important socio‐demographic market segments of their business. This research quantifies the significance and the contribution of such market segments to aggregate lodging demand in the USA. Finds that age distribution, income distribution, occupation and gender are the most significant socio‐demographic factors that have an effect on lodging demand. The aggregate lodging demand contribution of specific market segments obtained by combining the above factors pairwise, i.e. age and income, age and occupation, etc. is also discussed in the study.

This paper lays out the uses of demand curves, both for profit optimization, strategy, tiering and list price setting. This tool is also useful in public policy, such as extending health‐care coverage. It describes how to build a demand curve, and draw useful conclusions.

This paper provides examples of actual demand curves, and how they have been used for new product development, and in out‐maneuvering competitors. Examples are drawn from a number of industries, such as telecom, information services, insurance and electronics, and show how supply and demand are not static, but are highly interactive.

Companies and legislators are not familiar with the demand curves, despite its long history of use in academia. As a result of unfamiliarity with this tool, companies often make costly mistakes in estimates of new product uptake and volumes. If instead of demand curves they rely on price elasticities, companies deprive their senior management of a tool that suggests strategic responses to competitive situations. Surprisingly, many companies have never actually developed a demand curve for their markets.

This article allows managers have not actually seen a real demand curve to see one, and understand what this tool could do for them. It gives examples of new product development and tiering to address multi‐price level markets. In addition, it suggests how public policy makers should focus on shaping supply and demand, rather than imposing floors or ceilings on prices for health‐care coverage. Price ceilings today are responsible for widespread gaps in health care coverage. Finally, the literature on demand curves fails to show how supply and demand are highly interactive.

The purpose of this paper is to examine the possibility of an inverted U‐shaped relationship between job demands and work engagement, and whether social support moderates this relationship.

This study uses 307 technical and information technology (IT) managers who responded to an online survey. Multiple regressions are employed to examine linear and curvilinear relationship among variables.

Overall, results support the applicability of the quadratic effect of job demands on employee engagement. However, only supervisor support, not colleague support, moderated the relationship between job demands and work engagement.

The paper is the first to shed light on the quadratic effect of job demands on work engagement. The findings have noteworthy implications for managers to design optimal job demands that increase employee engagement.

Information science has existed in an uneasy, suspended, state of becoming for an uncomfortable number of years. Yet, despite a stubborn refusal to be born whole, hope for the imminent emergence of a fully fledged ‘science’ remains as fresh as ever. Conferences willingly consider and reconsider the question—what is information science? While some are content to search for the essence that is information science, others are convinced that they have already found it; there is no shortage of teachers ready to assert that information science consists of a particular (usually their own) mix of subjects. It is not uncommon to meet wandering, rather bemused, physicists, chemists and engineers eager to argue that they, too, have discovered something called information science. Members of this latter group may be uncertain of the precise nature of their discovery but are willing to aver that whatever it is it is not librarianship. In this struggle to induce the registrable birth of information science comparatively little attention is paid to the distinct social science bias of this most eclectic of ‘sciences’. This comparative neglect has persisted, surprisingly, despite a shared characteristic of fundamental significance. Both areas are noted for their incredible looseness of terminology and their confused and confusing professional thought and writing.