Technologies in caregiving: professionals’ strategies for engaging with new technology

This article explores the adoption of new technology in organisations that provide senior citizen care. Inspired by Niklas Luhmann’s systems theory, we study how technology reduces complexity by identifying client needs and ensuring predictability in service delivery. However, how technologies are adopted in practice is not determined by technology since it is also structured by care-workers' continuous decision-making. Against this backdrop, we explore how technologies alter the conditions for decision-making in two settings of elderly care, and we describe how care workers seek to adapt technologies to their practical needs as well as conception of care ethics. Developing a systems theory approach, the article eschews a priori assumptions of technological constraint on care-workers’ professional autonomy, offering a more open-ended exploration of diversified strategies for coping with new technology. Our case studies show that employees develop diversified strategies for technology adoption, including both non-usage, heated resistance, excessive embrace, and creative adaption.     

Is the system reliability profitable for retailing and consumer service of a dynamical system under cross-price elasticity of demand?

Retailing strategy is one of the most crucial factors for industries. A proper retailing strategy can help to enhance consumer service and increase the industry's profit. An improved approach to retailing is suggested in this research to deliver superior customer service while maximizing profits in a dynamic system. The study analyzes a retailing strategy for a demand with cross-price elasticity upon the retail price. A product's cross-price elasticity and the system reliability are critical factors in retailing. Understanding the cross-price elasticity of demand between products helps retailers to make pricing decisions that maximize profits by maintaining demand. Imperfect products are produced due to an imperfect production system. The imperfect ones must be adjusted with some costs to make them perfect for better retailing. The system failure rate is crucial for retailing under cross-price elasticity of demand patterns. Production system reliability, cross-price elasticity of demand, and consumer service are all essential factors that can impact a company's success in the market. The production rate is considered time- and system failure rate-dependent. Contradictory to the literature, a dynamical system is proposed for improved retail management, which is solved using the Euler-Lagrange theory. Finally, one can achieve the expected maximum profit for this retail system with optimum selling prices for different products by reducing the system failure rate. Some numerical illustrations with graphical representations are provided to validate the current study. Numerical examples show that applying cross-price elasticity of demand for more than two identical products provides 35% more profit for the retail industry than a single type of product.     

MODELING SOVEREIGN RISKS: FROM A HYBRID MODEL TO THE GENERALIZED DENSITY APPROACH

Motivated by the European sovereign debt crisis, we propose a hybrid sovereign default model that combines an accessible part taking into account the evolution of the sovereign solvency and the impact of critical political events, and a totally inaccessible part for the idiosyncratic credit risk. We obtain closed‐form formulas for the probability that the default occurs at critical political dates in a Markovian setting. Moreover, we introduce a generalized density framework for the hybrid default time and deduce the compensator process of default. Finally, we apply the hybrid model and the generalized density to the valuation of sovereign bonds and explain the significant jumps in long‐term government bond yields during the sovereign crisis.     

Effects of scale economies and production seasonality on optimal hub locations: the case of regional fresh produce aggregation

Interest in supporting local and regional food systems is rising and food hubs have attracted considerable attention among Federal, State, and local policymakers. This study explores the problem of endogenous hub location in fresh produce value chains in the Northeastern United States. To overcome limitations in the literature, we incorporate the effects of economies of scale and production seasonality into our models. Three experimental models are designed to examine the effects of alternatively applying yearly, quarterly, and monthly data on model solutions. We explicitly assess how interactions of scale economies and seasonality influence the structure and spatial attributes of an optimal regional produce aggregation hub system. The three models generate marketed different solutions and in many respects they lead to different conclusions about developing local/regional supply chains. The monthly model allows for production seasonality and actual hub operation cycle frequency and thus leads to more efficient hub solution with rich policy implications.     

Sensory Aspects of Retailing: Theoretical and Practical Implications

Sensory elements are an important aspect of both offline and online retail stores and can non-consciously influence consumer judgments and purchase behavior. In offline settings, ambient factors like scent, lighting, and music have been shown to influence customers’ shopping experiences and their buying behaviors. For online retail outlets, sensory factors related to color, display patterns, and layouts can have significant effects on consumer behavior. Sensory elements have strong managerial relevance since they can non-consciously influence behaviors and because they are relatively easy to change; for example, it requires minimal effort to change the lighting or the music at a physical retail store or the display pattern for an online store. The eight papers in this special issue address theoretical and practical issues related to how different sensory elements can strongly influence retail practices. These papers focus on underexplored topic areas and also on emerging technologies, which stimulate thoughts for further research in these areas.     

智慧居家养老服务协同供给的优化路径研究——以广西钦州市智慧居家养老项目的实践经验为例

智慧居家养老服务的协同供给可以形成社会联动效应，降低公共服务成本。运用公共服务协同供给分析框架，通过交叉分类方法从协同主体的利益与目标两个变量的耦合性出发分析广西钦州市智慧居家养老项目中养老服务主体间不同种类的协同关系，可以从加强政府领导、形成合作联盟、建立市场标准、创新扶持政策4个方面完善政府、企业、社会组织之间不同类型的协同供给，实现社会资源的高效利用以及向智慧居家养老服务的发展和转变。     

Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

Asymmetric information consolidation and price discovery: Inferring bad news from insider sales

Due to the paucity of sources of negative firm‐specific information, US capital markets have more difficulty identifying and incorporating bad news into stock prices than they do good news. Even though insider selling is a potentially important proxy for undisclosed bad news, researchers have difficulty ex ante identifying information‐based sales due to an inability to separate liquidity‐motivated from information‐based insider trades. We hypothesize that when insiders in multiple firms sell shares of one firm in which they are insiders and at the same time buy shares of other insider portfolio firms, the sale is more likely to be information‐based, since the proceeds are reinvested. Conversely, when an insider sells one firm without purchasing others or sells multiple insider firms the sale is likely liquidity‐motivated. We find that insider sales identified as information‐based using this algorithm are followed by significant negative abnormal returns. Information‐based sales are also more likely to be associated with delistings, earnings declines and earnings restatements. Analysts are also more likely to revise their earnings forecasts downwards for these firms. It is thus possible to ex ante identify insider sales with information content. Our results will be of interest to investors and also to regulators designing insider trading rules.     

An Empirical Analysis of Green Experiential Loyalty: A Case Study

The purpose of this study is to elaborate the structural relationships among the experiential quality dimensions, experiential trust, emotional attachment, experiential image, switching experience, experiential satisfaction, and experiential loyalty from the green perspective. The study findings are based on structural equation modeling (SEM) analysis of a convenience sample of 560 customers at one green restaurant in Taipei City, Taiwan. The findings show that investing resources in an increase in the experiential quality dimensions and a decrease in green switching experience is useful to enhance green experiential trust, green emotional attachment, green experiential image, green experiential satisfaction, and green experiential loyalty.     

阿莫西林克拉维酸钾片含量测定方法的改进

为解决实际应用中克拉维酸钾峰与后相邻杂质的分离度达不到要求的问题,建立了一种同时测定阿莫西林克拉维酸钾片中阿莫西林和克拉维酸钾含量的新方法,采用反相高效液相色谱法(RP-HPLC),Ultimate AQ-C_(18)色谱柱(4.6mm×250 mm,5μm),以pH值为4.4的0.05 mol/L磷酸二氢钠缓冲液为流动相,柱温为35℃,流速为1.0mL/min,检测波长为220nm。结果表明:阿莫西林和克拉维酸钾两主峰与相邻杂质得到完全基线分离,分离度大于1.5;克拉维酸钾对照品溶液质量浓度为0.050 0~0.500 1mg/mL时与峰面积的线性关系良好(r=0.999 8),平均回收率(n=9)为100.14%,RSD值为0.24%;阿莫西林对照品溶液质量浓度为0.100 0~1.000 1mg/mL时与峰面积的线性关系良好(r=0.999 9),平均回收率(n=9)为100.45%,RSD值为0.17%。与原有的《中华人民共和国药典》方法相比,新的阿莫西林克拉维酸钾片含量测定方法专属性好,准确度高,操作简便快捷,结果可靠,可作为一种质量控制方法。