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The intention of the empirics is to contribute to the general understanding of investor responses to market price shocks. The authors review assumptions about investor behavior in response to price shocks and investigate alternative rebalancing heuristics.

The authors use market data over 40 years to define market shocks. Portfolio rebalancing implements constrained Markowitz mean-variance (MV) heuristics.

Momentum rebalancing in portfolio management outperforms contrarian rebalancing in the study interval. Sensitivity analysis by decade, sector constraints and proportion of security holdings bought or sold continue to support momentum rebalancing.

The results are consistent with under-responding to price shocks at consensus levels in financial markets. The theoretical background provides a basis for experimental lab studies of shocks of different magnitudes under conditions in which participants have information on the levels of other participants and a condition in which they can only observe their previous estimates.

Managing portfolios in the face of price disturbances of different magnitudes is informed by empirical studies and their implications for investor behavior.

This is the first study the authors can locate that uses market data with alternative rebalancing heuristics to estimate price returns from the respective heuristics over a time interval of 40 years. The authors support the results with sensitivity estimates and consider implications for the underlying agent heuristics in light of background studies.

This study aims to conduct an empirical investigation to assess the hedge, diversifier and safe-haven properties of different environmental, social and governance (ESG) assets (i.e. green bonds and ESG equity index) vis-à-vis conventional investments (namely, equity index, gold and commodities).

The authors examine the sample period 2007–2021 using the bivariate cross-quantilogram (CQG) analysis and a dynamic conditional correlation (DCC) multivariate generalized autoregressive conditional heteroskedasticity (GARCH) experiment with several extensions.

The evidence shows that the analyzed ESG investments exhibit mainly diversifying features depending on the asset class taken as a reference, with some potential hedging/safe-haven qualities (for the green bond) in peculiar timespans. Therefore, the results suggest that investors might consider sustainable investing as a new measure of risk reduction, which has interesting implications for both portfolio allocation and policy design.

To the best of the authors’ knowledge, this study is the first that empirically investigates at once the dependence between different ESG investments (i.e. equity and green bond) with different conventional investments such as gold, equity and commodity market indices over a large sample period (2007–2021). Well-suited methodologies like the bivariate CQG and the DCC multivariate GARCH are used to capture the spillover effect and the hedging/diversifying nature, even in temporary contexts. Finally, a global perspective is used.

The case was developed from two 2-h interviews with the Chief Operating Officer of A-Basin, Alan Henceroth; there is no CEO of A-Basin. The second interview was recorded on a Zoom call to provide accuracy of quotations and information. A variety of secondary sources were used in terms of better understanding the current state of the ski industry, as well as its history.

Arapahoe Basin (A-Basin) is a historic, moderately sized, ski area with proximity to metropolitan Denver, Colorado. For over 20 years A-Basin partnered with Vail, allowing skiers to use the Vail Epic Pass, for which A-Basin received some revenue from Vail for each skier visit. The Epic Pass allowed pass holders unlimited days of skiing at A-Basin. More and more skiers were buying the Epic Pass, thus increasing the customer traffic to A-Basin. However, the skier experience was compromised due inadequate parking, long lift lines and crowded restaurants. The renewal of the contract with Vail was coming due, and A-Basin had to consider whether to renew the contract with Vail. The case is framed primarily as a strategic marketing case. The authors use Porter’s five forces model to assess the external environment of A-Basin, and the authors use the resource-based view and the VRIO tool to assess A-Basin’s internal strengths. Both frameworks provide useful analysis in terms of deciding whether to continue A-Basin’s arrangement with Vail or end the contract and pursue a different strategy. In 2019, after consultation with the Canadian parent company Dream, A-Basin made the decision to disassociate itself from the Epic Pass and Vail to restore a quality ski experience for A-Basin’s customers. No other partner had ever left its relationship with Vail. An epilogue details some of A-Basin’s actions, as well as the outcomes for the ski area. Generally A-Basin’s decision produced positive results and solidified its competitive position among competitors. Other ski areas have since adopted a similar strategy as A-Basin. A-Basin’s success is reflected in a pending offer from Alterra, Inc., to purchase the ski area.

The A-Basin case can be used in both undergraduate and graduate strategic (or marketing) management courses. It is probably best considered during the middle of an academic term, as the case requires students to apply many of the theoretical concepts of strategy. One of the best books to enable students to use Porter’s five forces is Understanding Michael Porter by Joan Magretta (Boston: Harvard Business Review Press, 2012). Magretta was a colleague of Porter for many years and was an Editor of the Harvard Business Review. For a discussion of the VRIN/VRIO concept, see Chapter 4 of Essentials of Strategic Management by Gamble, Peteraf and Thompson (New York: McGraw-Hill Education, 2019).

The e-commerce boom presents new challenges for last-mile delivery (LMD), which may be mitigated by new delivery technologies. This paper evaluates the impact of mobile parcel lockers (MPL) on costs and CO₂ equivalent (CO₂e) emissions in existing LMD networks, which include home delivery and shipments to stationary parcel lockers.

To describe customers’ preferences, we design a multinomial logit model based on recipients’ travel distance to pick-up locations and availability at home. Based on route cost estimation, we define the operating costs for MPLs. We devise a mathematical model with binary decision variables to optimize the location of MPLs.

Our study demonstrates that integrating MPLs leads to additional cost savings of 8.7% and extra CO₂e emissions savings of up to 5.4%. Our analysis of several regional clusters suggests that MPLs yield benefits in highly populous cities but may result in additional emissions in more rural areas where recipients drive longer distances to pick-ups.

This paper designs a suitable operating model for MPLs and demonstrates environmental and economic savings. Moreover, it adds recipients’ availability at home to receive parcels improving the accuracy of stochastic demand. In addition, MPLs are evaluated in the context of several regional clusters ranging from large cities to rural areas. Thus, we provide managerial guidance to logistics service providers how and where to deploy MPLs.

The tech giants Alibaba and Tencent compete on many fronts. This case focuses on three areas where they have competed very hard: new retailing, mobile payment, and ride-hailing. At the beginning of 2018, Alibaba and Tencent were gathering retail investments in bids to battle each other for shoppers' digital wallets. Key to the battle is China's mobile payment market, worth more than 200 trillion RMB, where Alibaba and Tencent are going head to head. The giants are not only directly competing in the payment platform area but also extensively fighting in other areas, such as ride-hailing, where they invested in and supported Didi and Kuaidi, respectively. To enhance understanding, this case also briefly goes through the history of the two giants. The purposes, methods, and consequences of their platform competition deserve an in-depth discussion

Inaction inertia occurs when people are less likely to act on a similar but inferior option after missing a superior opportunity, compared to if they had not missed out. This study aims to explore how promotional formats and their sequence affect the inaction inertia effect in online shopping, under the assumption of economic equivalence.

The authors performed two online experiments and analyzed the data by analysis of variance.

The findings indicate that, under the premise of economic equivalence: Monetary promotions exhibit a higher inaction inertia effect on consumers than nonmonetary promotions. When consumers miss a more favorable promotion and subsequently encounter a relatively less attractive one presented in a different promotional format, the inaction inertia effect is lower than when reencountering the same promotion format. When consumers miss a better monetary promotion and presently encounter a relatively less attractive nonmonetary promotion, the inaction inertia effect is lower than when they miss a superior nonmonetary promotion and currently encounter a relatively less attractive monetary promotion.

This study reveals the sequence effects of promotional formats, indicating that nonmonetary promotions following monetary ones effectively reduce inaction inertia. A strategically sequenced set of formats enhances consumer recommendations, mitigating inaction inertia. These findings open new research paths, providing insights into the impact of promotional format sequences on the inaction inertia effect. Consequently, this knowledge helps e-retailers in implementing effective promotional strategies and driving online purchases.

The purpose of this paper is to analyze the impact of the coronavirus (COVID-19) pandemic on participation and time allocated to work from home (WFH) by ethnic/racial group.

The authors employ USA time-use data [American Time Use Survey (ATUS)] for the 2017–2020 period and a parametric approach in their analysis.

Estimates show that the time allocated to WFH increased during COVID-19, especially for women. This increase is likely driven by more workers shifting to WFH (higher participation) rather than by longer hours worked by those who already teleworked. The authors also find relevant differences in the impact of COVID-19 on WFH by ethnic/racial group. Among ethnic/racial groups, only Asians increased WFH compared to White Americans. Within this ethnic group, the authors find significant differences across genders. Asian men increased participation in WFH, whereas Asian women increased both participation and hours worked, compared to White American women. Differences in this racial/ethnic group could be explained by previous research, which demonstrates a higher ability of Asians to perform job tasks remotely. However, this finding could also be attributed to an increase in discrimination during the COVID-19 pandemic.

This paper contributes to the recent and limited literature exploring the heterogeneous impact of COVID-19 on participation and time allocated to WFH by ethnic/racial group. Understanding the mechanisms driving vulnerable populations' abilities to work during socioeconomic downturns is of high policy importance.

This chapter discusses the significance and effectiveness of communication strategies in empowering marginalized communities. With a specific focus on reproductive health, this chapter examines the diverse scope of these strategies and their transformative potential. It explores the use of mass media as a dynamic tool for information dissemination and the adoption of information, education, and communication (IEC) approaches to enhance knowledge and awareness. Furthermore, this chapter highlights the catalytic role of social and behavior change communication (SBCC) in driving substantial transformations in behaviors and attitudes. An integral part of the discussion is the customization of communication strategies to effectively reach and empower marginalized communities in Bangladesh. Through these strategies, this chapter illuminates the path toward empowering marginalized communities.

The present study aims to comprehensively examine the impact of the Union Bank of Switzerland (UBS) takeover of Credit Suisse on the banking and financial services sector in the Indian stock market. To fully comprehend the impact of the event, the study separately investigates the response of private sector banks, public sector banks, overall banking companies and financial services companies to the takeover of the second-largest financial institution in Switzerland.

The study employs event study methodology, using the market model, to analyze the event's impact on Indian banking and financial services sector stocks. The data consists of daily closing prices of companies included in the Nifty Private Bank Index, Nifty PSU Bank Index, Nifty Bank Index and Nifty Financial Services Index from the National Stock Exchange (NSE). Furthermore, cross-sectional regression analysis has been conducted to explore the factors that drive abnormal returns.

The empirical findings of the study suggest the event had a heterogeneous impact on the stock prices of Indian banks and financial services companies. While public sector banks experienced a significant negative impact on select days within the event window, the overall Indian banking sector and financial services companies also witnessed notable declines. In contrast, Indian private sector banks were relatively resilient, exhibiting minimal effects. However, the cumulative effect is found to be insignificant for all four categories across different event windows. The study also observed that the cumulative abnormal returns (CARs) were significantly influenced by certain variables during different event windows.

To the best of the authors' knowledge, the present study is the earliest attempt that investigates the impact of the UBS takeover of Credit Suisse on the Indian banking and financial services sector using event study methodology and cross-sectional regression model.

The purpose of this paper is to explore the impact and mechanism of WeChat public platforms articles (abbreviated as WPP) on blood donation behavior using data of WPPA and donation behavior data.

This paper uses multiple linear regression methods, web crawlers and natural language processing technology. It first quantifies the impact of WPP published articles on donation behavior. On this basis, it then selects data from the day of article publication to further study the impact of article dissemination on donation behavior from the perspective of reading quantity, and analyzes the influencing factors of article reading quantity.

The results show that on the same day that an article is published, there is an increase of 13.8 and 14.3% in blood donation volume and fan registrations, respectively. The mediating effect exists. However, the day after an article is published, there is no longer any effect on blood donations. With a 1% increase in reading quantity, blood donation volume on the day of article publication increases by 0.13%, and this positive impact is promoted by the quality of the articles. A conc ise articles title and body and rich images help drive reading quantity. Moreover, blood donors prefer to read articles about blood dynamics and donation promotion, while articles about news, announcements and administrative affairs make them less inclined to read.

First, it focuses on WPPA, quantifies the impact of articles on blood donation behavior and analyzes the mechanism. Second, the authors study the impact and timeliness of social media article dissemination to address the insufficiency of existing research. Third, the study provides a scientific basis for the editing and publishing of articles, helping blood banks improve the effectiveness of publicity and recruitment.