Search results

In this paper, women entrepreneurs are seen as leaders and women leaders as entrepreneurial, making both groups an easy target of postfeminist expectations, governed by calls to embody the entrepreneurial self. Acknowledging that the entrepreneurial self has its roots in the universal, rational and autonomous subject, which was shaped in a male form during the Enlightenment, the purpose of this study is to conceptualise feminist resistance as a process through which the autonomous subject can be de-stabilised.

Empirically, this study draws on an extensive research project on women’s rural entrepreneurship that includes 32 in-depth interviews with women entrepreneurs in rural Sweden. This study interpreted expressions of resistance from the women by using an analytical framework the authors developed based on Jonna Bornemark’s philosophical treatise.

Feminist resistance unfolds as an interactive and iterative learning process where the subject recognises their voice, strengthens their voice and beliefs in a relational process and finally sees themselves as a fully fledged actor who finds ways to overcome obstacles that get in their way. Conceptualising resistance as a learning process stands in sharp contrast to the idea of resistance as enacted by the autonomous self.

This study helps researchers to understand that what they may have seen as a sign of weakness among women, is instead a sign of strength: it is a first step in learning resistance that may help women create a life different from that prescribed by the postfeminist discourse. In this way, researchers can avoid reproducing women as “weak and inadequate”.

Through the re-writing of feminist resistance, the masculine entrepreneurship discourse including the notion of the autonomous self is challenged, and a counternarrative to the postfeminist entrepreneurial woman is developed. Theorising resistance as a learning practice enables a more transforming research agenda, making it possible to see women as resisting postfeminist expectations of endless competition with themselves and others.

Flexible return policies are offered by the manufacturers to encourage the retailers announcing a lenient returns scheme to their customers.

This study considers the distribution of durable products in a supply chain where the demand is sensitive to sales effort and retail price. Using a game theoretic framework, the paper presents an assessment of the strategic effect of flexible returns policy announced by the manufacturer under retail competition and highlights its implications on profitability.

Comparative analysis of monopolistic and duopolistic competition provides a better understanding about the repercussions and related facts on offering a flexible returns policy in these environments. It is profitable for the manufacturer to offer a flexible returns policy when there is retail competition than under monopolistic condition.

Practitioners view returns policy offered as an insurance given to the buyers and they infer it to be a better mechanism for doing business. Lenient returns policy promotes the sales by increasing the trust on the retailer and boosts up the perception of quality about the product by lowering the perceived risk for customers.

Effective product return strategies such as being lenient in terms of time, money, effort, scope and exchange can result in increased revenues, lower cost and improved profitability to the manufacturer and retailer, at the same time offering an enhanced level of customer service.

The paper seeks to fill a research gap that concerns empirical studies on value‐based pricing in durable consumer goods. It aims to analyse the relationship between value for the customer and market prices in the washing machines market.

The customer value of a sample of 129 washing machine models is assessed through the conjoint analysis technique. It is then compared through a regression analysis to the market prices of the products.

The regression analysis reveals that the alignment between price and value for the customer is limited (only one of the two subsamples presents a positive dependence among the variables).

The study lacks explanatory power about the reasons for the misalignment between price and customer value in the investigated sector. The results, moreover, refer to a specific product category and a specific national market, although their representativeness as a mature durable in a mature market suggests a broader relevance of the implications. The size of the samples of the empirical research is also limited.

The paper provides an example and guidelines to practitioners on how to implement a customer value assessment. It provides practitioners a deeper understanding of the consequences of misaligned pricing, and of the potential of understanding the actual value sources for the customers.

The study empirically assesses the relationship between value for the customer and market prices of a category of mature durable goods. The results support the claim that value‐based pricing, although believed to be superior to other pricing policies, is still not established as a prominent practice. Moreover, the findings contribute to the discussion on the value of environment‐related attributes and their lifecycle monetary impact on the customers. It also identifies another possible obstacle to the adoption of value‐based pricing, i.e. the structure of the market, to be added to the ones reviewed in the literature.

Hospitality companies increasingly sell their unsold, or so-called rescued meals, on food waste reduction applications (e.g. Too Good To Go [TGTG]). The purpose of this research is to explore the influence of product construal and benefit appeals on consumer evaluations.

Study 1 (N = 277 participants) is an online experiment with a 2 × 3 between subject design analyzed using ANOVA and planned contrast analysis. Study 2 is a 2 × 2 field experiment (N = 147 sold rescued food boxes) using chi-square tests for the main analysis.

This study finds that an abstract product description (e.g. a magic box with an opaque content) matched with an environmental benefit appeal renders significantly higher consumer evaluations in comparison to when the same product is paired with financial benefits. In contrast, a concrete product presentation featuring financial benefits as opposed to environmental benefits increases consumer purchase intentions and willingness to pay.

We empirically show how the interaction and congruency between product construal and benefit appeals affect evaluations in a last-minute purchase context.

To the best of the authors’ knowledge, this is the first study to look at the interactive effect between product construal and benefit appeals in a food waste and technology context.

The use of price-based promotions is common in the service industry due to their positive impact on sales in the short run. To gain a better understanding of the effectiveness of various types of promotions, the current research aims to examine the contrasting effect of two popular framing methods (i.e. percentage-off versus dollars-off) on consumers' perceived savings and willingness to buy. More importantly, this research examines the moderating effect of personal sense of power on such relationships.

The study used 2×2 between subjects quasi-experimental design to test the hypotheses. Respondents were asked to read a scenario regarding booking a hotel room and then complete scales that measured their perceptions of savings and willingness to book.

Results indicate that personal sense of power moderates the effects of the promotion frame on perceived savings and willingness to book. Individuals with a low sense of power perceive significantly more savings and exhibit significantly higher booking intentions when the promotion is framed in dollars-off rather than in percentage-off format. The framing manipulation, however, had minimal effects among high power individuals. In addition, the authors find that confidence in estimating the promoted price is the psychological mechanism that potentially explains the casual link from power to perceived savings and willingness to book.

Drawing on the social psychology theory, the current study discovered some boundary conditions for the framing effect in the context of pricing of services. In addition, the current research advances the theoretical understanding of power's psychological and behavioural effects in the context of price promotions.

The paper focuses on high segments of the Italian wine market. The goal is twofold. First, it aims at understanding to what extent wine experts are influenced by specific quality clues. Second, it seeks at assessing the role and effectiveness of different quality clues in the creation of price

To meet these goals two independent equations are set. The first -estimated via an ordered logit- explaining the rating of a wine with a bunch of attributes of the wine and of its production process. The second equation is a hedonic price model –estimated via an interval regression- where price is a function of a large number of quality clues. The analysis covers 2,523 wines from three Italian Regions as reviewed by Veronelli guide, 2010 edition

The model estimation results indicates that: i) few attributes seems to systematically impact experts’ judgments; ii) many quality clues are associated with significant price premiums; iii) in some cases consumers give value to quality clues along with Veronelli’s experts while in other cases there is no such alignment

This study advances the literature in two different ways. First, modeling two distinct equations that describe the factors affecting, on the one side, experts’ evaluations, and, on the other side, market prices. Second, as it assesses the price premium associated to quality clues whose value hasn’t been considered so far in hedonic price models. We affirm that assessing factors that influence experts brings more transparency and a better segmentation in the guide market and in all experts’ quality signals.

This study aims to demonstrate how marketing analytics can be used to identify the challenges a B2B company faced in the conversion from a hard-copy print catalog to a digital ordering system. Specifically, an empirical research approach identified the potential issues the company was likely to face in the digitalization of the company’s catalog.

Using the Qualtrics survey platform, a questionnaire was used to obtain a final sample of 332 customers (a 14.02% response rate) on a variety of issues related to the transition from the company’s current printed catalog to a digital catalog ordering system. A variety of data analysis procedures were used to gain insight and highlight potential issues in the move to a digital format.

A variety of potential stumbling blocks were identified that suggest the company should move forward with caution. The data analysis was used to suggest areas that needed to be emphasized in the rollout of the new digital ordering system.

Like all marketing research, this application is limited by the methods used and the data generated by this study. Its implications suggest the potential use of marketing research before an important change in a B2B company’s marketing approach.

This paper provides an approach that can be used by firms considering a change to digitize key components of their marketing assets.

The research contributes to the B2B marketing literature by demonstrating how data-driven marketing analytics can be used to identify potential issues prior to the development of a new digital marketing approach used by B2B firms.

The purpose of this study is to assess how the information disclosed in prospectuses impacted the initial public offering (IPO) underpricing at a time of high government interference amid the ongoing pandemic.

The design of this study has several tracks, namely, a macro-level track, which is represented by the government measures to halt the pandemic; a micro-level track, which is followed by textual analysis of IPO prospectuses; and, finally, a machine learning track, in which the authors use state-of-the-art tools to improve their linear regression model.

The authors found that strict government anti-COVID-19 measures indeed contribute to the reduction of the IPO underpricing. Interestingly, the mere fact of such measures taking place is enough to take effect on financial markets, regardless of the resulting efficiency of such measures. At the micro-level, the authors show that prospectus sentiments and their significance differ across prospectus sections. Using linear regression and machine learning models, the authors find robust evidence that such sections as “Risk factors”, “Prospectus summary”, “Financial Information” and “Business” play a crucial role in explaining the underpricing. Their effect is different, namely, it turns out that the more negative “Risk factors” and “Financial Information” sentiment, the higher the resulting underpricing. Conversely, the more positive “Prospectus summary” and “Business” sentiments appear, the lower the resulting underpricing is. In addition, we used machine learning methods. Consisting of more than 580 IPO prospectuses, the study sample required modern and powerful machine learning tools like Isolation Forest for pre-processing or Random Forest Regressor and Light Gradient Boosting Model for modelling purposes, which enabled the authors to gain better results compared to the classic linear regression model.

At the micro level, this study is not confined to 2020, but also embraces 2021, the year of the record number of IPOs held. Moreover, in this paper, these were prospectuses that served as a source of management sentiment. In addition, the authors used a tailor-made government stringency index. At the micro level, basing the study on behavioural finance hypotheses, the authors conducted both separate and holistic analysis of prospectuses to assess investors’ reaction to different aspects of IPO companies as well as to the characteristics of the IPOs themselves. Lastly, the authors introduced a few innovations to the research methodology. Textual analysis was conducted on a corpus of prospectuses included in a study sample. However, the authors did not use pre-trained dictionaries, but instead opted for FLAIR, a modern open-source framework for natural language processing.