人力资本测算及其应用研究综述

从人力资本测算与相关理论、人力资本测算方法与相关应用两个方面的联系对人力资本测算及其应用研究进行总结，并展望未来可能的应用研究发展。人力资本测算和应用虽然得到前所未有的重视，大量的研究成果涌现，但远未达到成熟阶段，许多研究还有待深入和进一步的发展，更多的应用领域有待开发和拓展。     

Potential user factors driving adoption of IPTV. What are customers expecting from IPTV?

Internet Protocol Television (IPTV), the convergence services of television and Internet, is being rapidly developed around the world. The advent of digital technologies has changed the convergence market dramatically with the wide diffusion of the convergent services. Using the Technology Acceptance Model as a conceptual framework and method of logistic regression, this research analyzes the demand for IPTV by drawing data from 452 consumers. Individuals' responses to questions about whether they accept IPTV are collected and combined with observations of their socio-economic status and intrinsic/extrinsic factors modified from the Technology Acceptance Model. Results of logistic regression show two variables (intrinsic and extrinsic factors) that seem to explain what influences consumer behavior towards adopting IPTV. Overall, the logistic regression model explains over 50% of the variance in the IPTV adoption. The variances shed light on the multi-open platform environment that IPTV will forge.     

Drivers and barriers to cross-border e-commerce: Evidence from Spanish individual behavior

This paper explores the determinants of the individual's decision to perform cross-border e-commerce (CBeC). The European Union (EU) is especially interested in the promotion of CBeC because it is an important tool in its strategy to achieve the Digital Single Market in Europe. In this paper official data is used from a representative survey of 16,209 individuals on ICT usage by households and individuals that was carried out in Spain by the National Institute of Statistics (INE) for the year 2016. Using a standard neoclassical utility maximization framework, and logistic regression techniques, the results show that being a male is positively related to the probability of practicing CBeC. Education is positively and significantly related to the probability of being involved in CBeC with EU countries. Computer and Internet Skills are significant and positive factors in explaining CBeC (either with EU countries or with the rest of the world). The variable “how often the consumer sees other customer reviews before buying online”, has a positive effect. Foreign nationality also increases the likelihood of using CBeC. To promote CBeC in Spain measures towards developing digital skills, Internet trust and use of online information reviews of goods and services are discussed.     

Imagining futures: A collaborative policy/device design for wearable computing

The rapidly expanding market for wearable computing devices (wearables), driven by advances in information and communication technologies (ICT), wireless access, and public acceptance of a design aesthetic, is indicative of the near limitless potential for changing the relationship of users to information context(s). As the adoption of wearable devices spreads, there are cultural and social impacts that represent both barriers and opportunities, with subsequent policy ramifications. All too often designers, technologists, and policymakers operate independently developing products that are out of sync, lack interoperability, or are hindered by well meaning, but obstructive policy. This paper proposes a futures-based, iterative policy-informed design framework for developing wearable devices that guides interdisciplinary collaborators early in the process of designing a research & development plan. This approach allows for the development of “images of the future” through which various potential implications and effects of device design in social, technological, and regulatory contexts can be explored.     

Analysing customers' reviews and ratings for online food deliveries: A text mining approach

The purpose of this study was to explore the relationship between online reviews and ratings through text mining and empirical techniques. An Indian food delivery portal ( Zomato.com ) was used, where 50 restaurants on Presence Across Nation (PAN) basis were selected through stratified random sampling. A total of 2530 reviews were collected, scrutinized, and analysed. Using the NVivo software for qualitative analysis, seven themes were identified from collected reviews, out of which, the ‘delivery’ theme was explored further for identifying sub-themes. Linear regression modelling was used to identify the variables affecting delivery ratings and sentiment analysis was also performed on the identified sub-themes. Regression results revealed that hygiene and pricing (delivery subthemes) demonstrated lower delivery ratings. These variables can be established as indicators for restaurants and related online food delivery services to build their business model around them. Similarly, negative sentiments were observed in pricing and hygiene sub-themes. Restaurants and online food services can enhance hygiene levels of their food delivery process in order to receive higher delivery ratings. Similarly, pricing of food items can be modified such that customers are not deterred from ordering the items—food and ordering service do not become cost-prohibitive. This study devised a standardized methodology for analysing vast amounts of online user-generated content (UGC). Findings from this study can be extrapolated to other sectors and service industries such as, tourism, cleaning, transportation, hospitals and engineering especially during the pandemic.     

The benefits and implementation of performance transparency: The why and how of letting your customers ‘see through’ your business

While some organizations swear by the benefits of transparency and are eager to learn and implement transparency practices, many managers are still reluctant or even afraid to use them. Our research reveals that only a few innovative companies have taken steps to leverage a potentially useful form of transparency: the provision of accessible and objective information to customers (e.g., sharing unbiased benchmark data, publishing unfiltered customer comments, or providing candid product reviews that may praise but also criticize the company’s products). Our study also shows that many companies remain wary and view greater calls for transparency as a challenge to be managed rather than an opportunity to be traded upon. This is partly due to limited research into the performance benefits of giving customers access to objective information, and lack of practical guidelines on how to actually implement it. This article addresses these shortcomings. First, we investigate whether performance transparency leads to customer outcomes that can be profitable for an organization and, second, we analyze the characteristics of successful transparency initiatives in a wide range of industries. Our research shows that customers exhibit more trust and are willing to pay a premium to deal with transparent businesses. Also, it uncovers seven effective strategies to leverage transparency. This article provides convincing empirical evidence for the benefits of performance transparency and the ways in which management may implement it successfully.     

国内外饭店职业经理人研究综述

我国对饭店职业经理人的研究从理论到实践两个方面都滞后于市场经济发达国家。中外职业经理人出现的经济背景和社会条件不同,研究的关注点差别较多。国外的研究最早关注于经理人角色、继而关注总经理的管理能力、经理人职业路径、经理人与雇主关系、经理人薪酬体系和经理人胜任力模型等。国内的研究则关注于饭店职业经理人界定、能力与素质、市场化问题、队伍建设与发展,近两年才出现饭店职业经理人角色研究。同时,在研究方法上还存在着以宏观研究为主,微观研究不足,定性研究较多,定量研究不够,研究方法单一,缺少对相关理论的系统研究和集合的问题。国内外研究者在研究内容、层次、视角上的差异,其实质反映了饭店职业经理人生存与发展的环境差异,即市场经济成熟度的差异。     

How Online Product Reviews Affect Retail Sales: A Meta-analysis

A growing body of research has emerged on online product reviews and their ability to elicit performance outcomes desired by retailers; yet, a common understanding of the performance implications of online product reviews has eluded us. Scholars continue to navigate an array of studies assessing different design elements of online product reviews, and various research settings and data sources. We undertake a meta-analysis of 26 empirical studies yielding 443 sales elasticities to examine how these variables relate to retail sales. Building on well-established meta-analytical methods, we address the following questions: How does review valence influence the elasticity of retailer sales? What about review volume? For which product types and usage situations do online product reviews have a greater impact on retailer sales elasticity? Which types of online reviewers and websites exert the greatest influence on retailer sales elasticity? Our study answers these important questions and provides a much needed quantitative synthesis of this burgeoning stream of research.     

Empowering the new traveller: storytelling as a co-creative behaviour in tourism

The work proposes a theoretical and empirical model that investigates how storytelling is a powerful co-creative behaviour in tourism. The contribution takes a step forward from the classical theories on co-creation and develops the case where consumers act almost independently from traditional brands. The empirical study adopts an interpretive approach to analyse online travel reviews. Data are interpreted through Yi and Gong's model on consumer value co-creation behaviour [(2013). Customer value co-creation behavior: Scale development and validation. Journal of Business Research, 66, 127], the Phase dynamics theory of travel epiphany behaviour [Woodside, A. G., & Megehee, C. M. (2010). Advancing consumer behaviour theory in tourism via visual narrative art. International Journal of Tourism Research, 12(5), 418–431], and the Archetype theory [Woodside, A. G., Sood, S., & Miller, K. E. (2008). When consumers and brands talk: Storytelling theory and research. Psychology & Marketing, 25(2), 97–145]. The study indicates that storytelling behaviours in value co-creation activate a ‘customer delight' response, which is an affect-based construct.     

Comparative study of deep learning models for analyzing online restaurant reviews in the era of the COVID-19 pandemic

Online reviews remain important during the COVID-19 pandemic as they help customers make safe dining decisions. To help restaurants better understand customers’ needs and sustain their business under current circumstance, this study extracts restaurant features that are cared for by customers in current circumstance. This study also introduces deep learning methods to examine customers’ opinions about restaurant features and to detect reviews with mismatched ratings. By analyzing 112,412 restaurant reviews posted during January-June 2020 on Yelp.com, four frequently mentioned restaurant features (e.g., service, food, place, and experience) along with their associated sentiment scores were identified. Findings also show that deep learning algorithms (i.e., Bidirectional LSTM and Simple Embedding + Average Pooling) outperform traditional machine learning algorithms in sentiment classification and review rating prediction. This study strengthens the extant literature by empirically analyzing restaurant reviews posted during the COVID-19 pandemic and discovering suitable deep learning algorithms for different text mining tasks.