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Hospitality HR and Big Data: Highlights from the 2015 Roundtable
Get PDFThe effects of so-called big data, which involves a torrent of detailed information about employees and customers, have begun to ripple through hospitality human resources—allowing managers the potential to connect HR policies with corporate financial results. As discussed in this inaugural roundtable on “Hospitality HR and Big Data,” hospitality firms are gradually addressing both the possibilities and the challenges of this mountain of data. In addition to dealing with the volume of data, hospitality firms must cope with the velocity, variety, and veracity of the data, while they also ensure ethical application of the information they gather. Given the size of HR databases, it’s possible to draw statistically valid conclusions from analytical procedures, but care must be taken to ensure that those results make business sense before taking actions based on such analyses
Surprise, Anticipation, and Sequence Effects in the Design of Experiential Services
No full textThe most salient or peak aspect of a service experience often defines customer perceptions of the service. Across two studies, using the same novel form of a scenario-based experiment, we investigate the design of peak events in a service sequence by testing how anticipated and surprised peaks influence customer perceptions. Study 1 captures the immediate reactions of participants and Study 2 surveys participants a week later. In both studies we find a main effect for the temporal peak placement, confirming the positive influence of a strong peak ending. When assessing the peak design strategies of surprise and anticipation, we find in Study 1 that surprise and anticipation moderates the temporal peak placement (e.g., early peak versus late peak) on overall customer perceptions, with the surprise peak at the end of an experience yielding the strongest effect. In Study 2 we see that the remembered experience of a surprise peak positively affects customer perceptions compared to an anticipated peak regardless of the temporal placement of the peak. We also find that the infusion of a surprise peak ending has a lasting effect that amplifies the peak-end effect of remembered experiences. Drawing on these findings, we discuss the role of surprise, anticipation, and sequence effects in experience design strategy
The Effect of Service Complexity on Performance of Franchised Outlets
Get PDFThe overall results of this study suggest that for low service complexity new ventures the incentive structures and contractual arrangements inherent in franchising are well suited. In service ventures with high levels of service complexity, arrangements involving two distinct parties that must work together may be more costly and difficult to manage. We find that franchisee outlets outperform independent entrepreneurs in each of the first three years of operation when the service business was low in complexity. In contrast, independent operators were able to outperform franchisees after the first year in complex service enterprises. Franchisors who operated in complex service settings were only able to outperform independents in the first year of operation, suggesting that both experienced chains who provide reliable and consistent services and independent entrepreneurs who quickly learn to adapt to the broad needs of sophisticated consumers are able to obtain performance success
Understanding Customer Value in Technology-Enabled Services: A Numerical Taxonomy Based on Usage and Utility
Get PDFUse of technologies in service encounters can enhance service delivery and increase customer satisfaction in services. Our research develops a numerical taxonomy that provides a deeper understanding of usage and value of customer-facing technology-based innovations in the U.S. restaurant industry. In this study, utility is a proxy for intrinsic customer value. Usage was estimated by past visits to restaurants and utility was calculated by using a specific type of discrete choice experiment known as Best-Worst (or max-diff) experiment. We offer insights for service strategy technology choices and customer value in service delivery systems research and practice. Furthermore, we advance service science by discussing the inherent management pitfalls of failing to distinguish between technology usage and utility in services
Construing a Transgression as a Moral or a Value Violation Impacts Other Versus Self-Dehumanisation
Get PDFWhat determines whether people dehumanise another person or themselves? We propose that the construal of a violation as moral or value-based influences who is dehumanised. Previous research has demonstrated that people perceive morals to be objective indicators of right and wrong (Goodwin amp; Darley, 2008), while values are viewed as subjective (Bardi amp; Schwartz, 2003). Here, participants recalled past moral or value violations, then reflected on the thoughts and feelings of either the other person victimised by their violation, or their own thoughts and feelings. Participants then rated dehumanisation of either the other or themselves using the Human Nature and Uniqueness Scale. We found that participants dehumanised the other more when recalling a value violation. This result suggests that differences in construal between morals and values can have an impact on dehumanisation
Restaurant Reservations Optimization Tool
No full textThe purpose of this tool is to determine the best mix of tables in a restaurant, while simultaneously determining which reservations should be accepted from forecasted demand. A key parameter in the tool is the degree to which average dining durations are inflated. The tool user selects this inflation factor according to expectations regarding the extent to which parties will exceed the anticipated average dining time. Lower inflation factors result in more revenue, because more reservations are accepted, but also come with lower service levels, meaning more customers will need to wait for a table. Based on the user inputs, the tool, which uses the Solver add-in for Microsoft Excel, returns the optimum table mix for the greatest revenue
Attention Effects in a High-Frequency World
Get PDFHow does limited attention affect stock prices in today’s computer-driven financial markets? We study this issue by re-examining the effects of limited attention using a dataset that separately identifies trades made by high-frequency traders (HFTs, or computers) versus those made by non-high-frequency traders (human decision-makers). We employ a set of six attention proxies to identify earnings announcements with low investor attention: announcements made on Fridays and on days with multiple earnings announcements, and announcements with slow analyst forecast adjustments, high news distraction, low EDGAR download volume, and low Google search volume. Across multiple attention proxies, we find that HFT trading improves the responsiveness of prices by increasing the short-horizon price response and reducing the long-term price drift following earnings surprises, diminishing the inefficiencies previously observed around low-attention announcements by 69% to 100%. We find that the price efficiency improvements are more closely tied to HFT liquidity demand than supply, suggesting that HFTs improve efficiency by processing and trading on the information in low-attention announcements
How the Deepwater Horizon Oil Spill Damaged the Environment, the Travel Industry, and Corporate Reputations
Get PDFIn July 2015, BP Oil Corporation agreed to pay a fine of $18.7 billion for its role in the 2010 oil spill in the Gulf of Mexico, caused by the rupture of BP’s Deepwater Horizon well. These funds are earmarked for continued recovery of the coast of the five states affected by the spill, Texas, Louisiana, Mississippi, Alabama, and Florida.1 The spill caused substantial damage to the Gulf Coast’s environmental quality, to the coast’s tourist volume, and to BP’s corporate reputation. Since that time, BP has sought to repair both the coast and its reputation, while encouraging tourists to return to the beaches and bayous that were covered with oil. In this report, we examine these respondents’ view of BP’s corporate reputation and the outcomes for travel to the white sand beaches of Florida’s panhandle
Environmental Sustainability in the Hospitality Industry: Best Practices, Guest Participation, and Customer Satisfaction
No full textCertain sustainability practices could be considered nearly universal in the lodging industry, based on a study of 100 resorts in the United States. Among the common green practices are water conserving fixtures and linen-reuse programs. A separate survey of 120,000 hotel customers finds that guests are generally willing to participate in sustainability programs, but the presence of green operations still do not override considerations of price and convenience in selecting a hotel. Additionally, the study finds an increased willingness to participate when hotels offer incentives, such as loyalty program points, for participating in environmental programs. Although the link between environmentally sustainable programs and improved customer satisfaction is weak compared to standard drivers like facilities, room, and food and beverage quality, hotels are increasingly expected to maintain sustainability programs as a regular feature of their business. At the same time, the study did find that environmental sustainability programs do not diminish guest satisfaction. Consequently, the decision regarding which programs to implement should rest on cost-benefit analysis and other operating considerations
An Evaluation of Integer Programming Models for Restaurant Reservations
No full textA notable difference in rooms (hotel) revenue management reservations versus table (restaurant) revenue management (TRM) reservations is the variation that occurs in duration. In the hotel setting, durations are explicit in the reservation itself: a stay of a specified number of nights. In restaurants, by contrast, there is a natural variation in the amount of time parties are at the table. This duration variation presents interesting challenges to TRM. Dealing with these challenges is our goal in the article. Specifically, we introduce and evaluate 10 different models for restaurant capacity and reservations, five each of two different types. In one type of model, tables are pooled and parties are not explicitly matched to tables; in the other parties are matched to specific tables. The objective is to maximize revenue (or contribution) from known reservation demand. Variables are both the mix of tables in the restaurant and the reservations accepted. An important ancillary goal we have is to evaluate the effectiveness of the models from the perspective of customers, specifically examining whether a table is ready for them at the time of the reservation, an issue of high importance to restaurant patrons. Of the 10 models, seven define a pareto frontier between revenue and service; of those seven, five are pooling models. We use this frontier to offer advice to restaurateurs looking to better manage reservations