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This study aims to examine consumer perception during COVID-19 and identifies cruise industry marketing strategies to fill a gap in crisis management and product pricing literature.

This study developed and validated two-factor measurement scales (vaccine perception and protective behavior), which predicted cruise intents well. This study revealed how geo-regional factors affect consumer psychology through spatial analysis.

This study recommended pricing 7-day cruises at $1,464 (the most preferred length). The results also showed that future price hikes would not affect demand and that coastal marketing would help retain customers.

This study contributed to the business, hospitality and tourism literature by identifying two new and unique factors (vaccine perception and protective behaviors), which were found to affect consumers’ intention to travel by cruise significantly. The result provided a better understanding of cruise tourists’ pricing preferences and the methods utilized could easily be applied to other cruise markets or tourism entities.

This paper gives a model of collusion formation and a method of measuring the degree of it among the traders/bidders in the agricultural commodity markets in India. The important assumption is that the bidding is repetitive with a set of common bidders. The theory has been derived based on the behavior of the wholesale market of agricultural commodities in India. The paper is based on full information in the collusion formation. The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data.

The paper used the standard theory of optimization and the theory of auction and probability statistics.

This is a complete information model of cartel formation. The bidding is repetitive and continues forever in discrete time. Hence bidders behavior is observable. Using the proposed method, if the APMC measures for each market and publishes on a periodic basis, say weekly basis, then it will be easier to break the collusion in the market where relative collision is present. For example, if a farmer has three options to sell in three different markets, then the published data would help them to select the market where the degree of collusion is relatively lower. Moreover, the undesirable loss can be avoided based on the right choice of market. As a result, transaction costs will be optima.

The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data.

The learning outcomes of this study are as follows:

1. the benefits of differential pricing over uniform pricing;

2. the differences between second- and third-degree price discrimination;

3. the rationale for charging different prices for segments having different willingness to pay; and

4. how different prices for the same product can lead to perceptions of unfairness and how companies might manage such an issue.

This case outlines the decisions that Adar Poonawalla, the CEO of Serum Institute of India (Serum), had to make in late April 2021 concerning its pricing for the COVID-19 (Covid) vaccine. Serum was the world’s largest manufacturer of vaccines, and its Covishield vaccine had received regulatory approval, but faced an unusual challenge and opportunity. In most countries, governments had procured Covid vaccines from manufacturers and then delivered the vaccines to consumers free of cost. But in India, there was a three-tier pricing system. While the Government of India had committed to free vaccines in government-run public hospitals, it also allowed vaccine makers to directly sell vaccines to state governments, as well as private hospitals, who were at liberty to charge consumers for the vaccines. This created an interesting pricing dilemma for Serum: as different customers had different willingness to pay, should Serum use differential pricing? Would such a tiered pricing system be considered fair? How many different price points should Serum maintain? By exploring these and related decisions that Poonawalla had to make, the case is intended to teach price discrimination.

The case is intended for graduate-level courses in marketing, pricing and economics. This case illustrates the principles of differential pricing/price discrimination. More specifically, it highlights pricing strategies motivated by second- and third-degree price discrimination in an emerging market’s health-care context. From the information in the case, the student can learn to apply the concepts of second- and third-degree price discrimination in marketing. After working through the case and assignment questions, instructors will be able to help students understand the following concepts:

Teaching objective 1: the benefits of differential pricing over uniform pricing.

Teaching objective 2: the differences between second- and third-degree price discrimination.

Teaching objective 3: the rationale for charging different prices for segments having different willingness to pay.

Teaching objective 4: how different prices for the same product can lead to perceptions of unfairness and how companies might manage such an issue.

Teaching notes are available for educators only.

CSS 8: Marketing

This study aims to propose a risk-induced game theoretic forecasting model to predict average daily rate (ADR) under COVID-19, using an advanced recurrent neural network.

Using three data sets from upper-midscale hotels in three locations (i.e. urban, interstate and suburb), from January 1, 2018, to August 31, 2020, three long-term, short-term memory (LSTM) models were evaluated against five traditional forecasting models.

The models proposed in this study outperform traditional methods, such that the simplest LSTM model is more accurate than most of the benchmark models in two of the three tested hotels. In particular, the results show that traditional methods are inefficient in hotels with rapid fluctuations of demand and ADR, as observed during the pandemic. In contrast, LSTM models perform more accurately for these hotels.

This study is limited by its use of American data and data from midscale hotels as well as only predicting ADR.

This study produced a reliable, accurate forecasting model considering risk and competitor behavior.

This paper extends the application of game theory principles to ADR forecasting and combines it with the concept of risk for forecasting during uncertain times.

This study is the first study, to the best of the authors’ knowledge, to use actual hotel data from the COVID-19 pandemic to determine an appropriate neural network forecasting method for times of uncertainty. The application of Shapley value and operational risk obtained a game-theoretic property-level model, which fits best.

While most marketing research on organic products refers to the premium price levels of organic products, little research exists on consumers’ behavioural responses to price promotions or discounts of organic products. The present study aims to fill this research gap.

To develop alternative hypotheses about consumers’ behavioural responses to price promotions of organic fast-moving consumer good (FMCG) products, the authors used the researcher-introspection method in a pre-study. To test the hypotheses developed based on the pre-study, the authors conducted a field experiment on online advertising of an FMCG sold in drugstores. In the field experiment, the authors exposed consumers to an online ad featuring either a price promotion (−20%) or the regular price of the product. The ads also varied in terms of whether they contained explicit organic claims or not, and whether they included implicit organic cues or not.

The price promotion increased the clickthrough rate of the ad both when combined with an explicit organic claim and when combined with the implicit cue of green product pack. The results suggest that consumers do not have significant suspicions about price promotions of organic products, but rather presume that the price promotion of an organic FMCG product is a periodical promotional action, similar to the price promotions for conventional, non-organic products. Also, consumers seem to assume that the regular prices of organic FMCG products are so high that the retailer/manufacturer can well afford periodic price discounts.

The present research shifts the focus of organic marketing research from the premium price levels to the effectiveness of price promotions and discounts. Further, the present results contrast with certain earlier studies that have questioned the effectiveness of price promotions for organic products.

The results have different implications for marketing managers of brands not yet providing organic product versions in the market, of brands producing non-organic products, which cannot easily be rendered organic, and of brands offering organic products in the market.

This is, to the best of the authors’ knowledge, the first empirical study and field experiment on price promotions of organic products, including explicit organic claims.

Although the effects of both news sentiment and expectations on price in financial markets have now been extensively demonstrated, the jointness that these predictors can have in their effects on price has not been well-defined. Investigating causal ordering in their effects on price can further our understanding of both direct and indirect effects in their relationship to market price.

We use autoregressive distributed lag (ARDL) methodology to examine the relationship between agent expectations and news sentiment in predicting price in a financial market. The ARDL estimation is supplemented by Grainger causality testing.

In the ARDL models we implement, measures of expectations and news sentiment and their lags were confirmed to be significantly related to market price in separate estimates. Our results further indicate that in models of relationships between these predictors, news sentiment is a significant predictor of agent expectations, but agent expectations are not significant predictors of news sentiment. Granger-causality estimates confirmed the causal inferences from ARDL results.

Taken together, the results extend our understanding of the dynamics of expectations and sentiment as exogenous information sources that relate to price in financial markets. They suggest that the extensively cited predictor of news sentiment can have both a direct effect on market price and an indirect effect on price through agent expectations.

Even traditional financial management firms now commonly track behavioral measures of expectations and market sentiment. More complete understanding of the relationship between these predictors of market price can further their representation in predictive models.

This article extends the frequently reported bivariate relationship of expectations and sentiment to market price to examine jointness in the relationship between these variables in predicting price. Inference from ARDL estimates is supported by Grainger-causality estimates.

The study aims to investigate how attribution theory in the context of pricing strategies can help tourism destinations recover from the negative impacts of the COVID-19 pandemic.

The study adopted a qualitative research design using semi-structured interviews to address the lack of research in this area. Interview participants included tourists and tourism customers. The interview responses were then analyzed using “Nvivo” qualitative data analysis software to identify critical themes regarding applying attribution theory to pricing strategies.

The findings revealed that tourists prefer bundled and hedonic pricing strategies that integrate the service providers' pricing strategies' locus of control, stability and controllability. Tourists do not favor dual pricing strategies unless the reasons for price controllability or stability are justified. Tourists also prefer the controllable pay-what-you-want pricing strategy. Although tourists accept dynamic pricing, certain conditions related to price locus, stability and controllability must be met.

The research shows tourists prefer pricing strategies that give them control and flexibility, like bundled packages and pay-what-you-want models. Service providers should integrate pricing strategies that transparent costs and justify price fluctuations. While dynamic pricing is accepted if necessitated by external factors, tourists are wary of unnecessary price changes. Providers can build trust and satisfaction by explaining pricing rationale and offering controllable options like bundles.

The study contributes to the theory by applying attribution theory to the context of pricing strategies in tourism. It also provides innovative recommendations for tourism managers on how to use pricing strategies after the COVID-19 pandemic. The findings offer new insights that extend beyond previous research.

The case has been developed by using secondary sources of information.

Tesla’s much-awaited foray into the burgeoning Indian electric vehicle (EV) marketplace had hit the “high import tariff” roadblock. Discussions ensued and finally, Elon Musk, the CEO of Tesla and the Indian Government found common ground. The moot point of Tesla’s entry mode was resolved. Musk announced Tesla’s plan to set up an EV supply chain and manufacturing facility in the host country. This case discusses factors affecting location decision, market entry modes and international corporate-level strategies. Tata Motors sold affordable cars and was miles ahead in the EV race in India. Musk had to align Tesla’s India strategy with the company’s global strategy to woo the price-sensitive Indian consumers. What were the options available to him? This case examines different business-level strategic options that could help Tesla drive in the fast lane in India.

The case can be used in international strategy course at graduate level. It can also be used in a session on international marketing in marketing management course.

Chewy, Inc. is a direct-to-consumer seller of pet food and supplies. Their approach involves a deep understanding of pet owners’ needs and behaviors to provide personalized product recommendations and exceptional customer service. This case study aims to describe Chewy’s growth strategies and how the company can remain a market leader.

Using the customer value assessment tool, the authors examine Chewy’s value proposition, including service, quality, image and price strategies.

Chewy has built a loyal customer base that values the company’s commitment to their pets’ health and well-being. Future opportunities include focusing on pet wellness products and services, collaborating with veterinary providers in telemedicine and international expansion.

This work is largely conceptual and presents a descriptive case study which reviews Chewy’s marketing strategy based on industry research as well as a customer value assessment via the service-quality-image-price framework.

Corporate leaders must adapt to market change and create business strategies to deliver superior value for customers. This requires innovative products, services and processes. The strategic insights are applicable to retailers, service and technology firms and entrepreneurial companies seeking to scale their businesses.

Chewy’s highly competitive market includes Amazon, e-commerce pet supply companies and big-box pet stores. But it has dominated the online sector and has substantial growth prospects. This paper concludes with recommendations for management and questions for consideration.

This study aims to adopt a holistic approach to understand cruise revenue management (RM) practices that cover ticket and onboard revenues, through a cross-disciplinary literature review and practitioner interviews. An integrated cruise RM framework was developed and served as a blueprint for future cruise studies and practices.

A multi-stage approach was adopted, including a systematic literature review, two-waves of interviews with 26 cruise industry practitioners and the development of a holistic RM framework.

This study clarifies cruise RM functions across product planning, delivery stages and identifies ticket and onboard RM components. These are incorporated into the integrated framework, with weather and itinerary/ route attractiveness as additional considerations. Interviews revealed that there is no difference in the RM cycle before and during the COVID-19 pandemic, although strategies and tactics may vary in response to the market situation.

Suggestions are made regarding product and service bundling and ways for ticket and onboard revenue teams to work together to optimize total revenue. Future research directions are also provided under the categories of RM applications and concepts, ticket core activities, onboard core activities and overall issues.

To the best of the authors’ knowledge, this is the first paper to conduct a cross-disciplinary systematic literature review of cruise RM without imposing publication dates or specific databases and the first to develop an integrated cruise “total” RM framework that includes ticket and onboard revenues.