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This study aims to explore the underlying mechanism and boundary conditions of consumer’s preference on a multiple-percentage discount over an economically equivalent single discount.

The authors tested their predictions using two large-scale online experiments accompanied by a fully controlled laboratory experiment.

This study shows that the preference for a multiple-percentage discounts over an economically equivalent single-percentage discount is because consumers directly add the raw values of multiple-percentage discounts. The preference is less prominent if the percentage discounts are presented using round (vs non-round) numbers and is strengthened by experiential-thinking style.

This study examined consumer preferences between a single-percentage discount and an economic equivalent multiple-percentage discount. A promising research topic is exploring consumer preferences between multiple-percentage discounts.

Understanding how different presentation formats of the same price discount can lead to different evaluations enables managers and marketers to ensure a more effective promotional strategy.

This study extends literature on price-based promotions by demonstrating how consumers’ preferences for multiple discounts can be strengthened or weakened.

This paper aims to explore the impact of green finance on the heterogeneity of enterprise green technology innovation and the underlying mechanism between them.

Using the data of China's A-share listed enterprises from 2008 to 2020 and the fixed effect model, the authors empirically explore the relationship and mechanism between green finance and green technology innovation by constructing the green finance index while considering both the quality and quantity of innovation.

The study suggests that green finance is positively related to the quality and quantity of enterprise green technology innovation, while green finance is more effective in stimulating the quality of green technology innovation than quantity. In addition, alleviating financial mismatch and improving the quality of environmental information disclosure are core mechanisms during the process of green finance facilitating green technology innovation. Furthermore, green finance exerts a more positive effect on the quality and quantity of green technology innovation with large-size enterprises, heavily polluting industries and enterprises in the eastern region.

This paper enriches the literature on green finance and green technology innovation and provides practical significance for green finance implementation.

The digital economy has become a new engine for economic development, promoting the upgrading and transformation of traditional industries as well as fostering emerging industries and forms of business. Nonetheless, how does the digital economy affect innovation? The research objective is to explore the specific impact of the digital economy on innovation output.

This paper innovatively adopts the dynamic panel data model (DPDM) to carry out an empirical study on the impact of the digital economy on innovation output, through the observation of 30 provincial-level administrative regions in China. Furthermore, the paper innovatively analyzes the impact of different dimensions of the digital economy on innovation output and the impact of the digital economy on different dimensions of innovation output.

It is found that the digital economy is conducive to boosting innovation output considering innovation continuity. Specifically, the driving impact of core industries and enterprise application of digital economy on innovation output is more prominent, but the driving impact of infrastructure and personal application on innovation output is not fully played. Meanwhile, the driving impact of the digital economy on the innovation output quality is more significant than that digital economy on the innovation output quantity.

This study employs a DPDM for the first time to investigate the specific impact of the digital economy on innovation output, and contributes to the existing literature on the digital economy and digital economy-driven innovation. The findings offer a comprehensive explanation for the impact of the digital economy on innovation output, which has reference value for the formulation of innovation policies driven by digital economy, thereby providing impetus for the sustained and stable development of China's economy.

Studies have shown that research is a global innovation’s “engine room.” Therefore, young adult-built environment researchers (YABER), especially in developing countries, need research upskilling and reskilling training for better-integrated outcomes. Evidence shows that research training can improve YABER competencies and proficiencies. In Nigeria, YABER may have had some challenges in training needs. There is a lack of extant literature about the issues facing Nigeria’s YABER upskilling and reskilling training needs. Thus, this study investigated the perceived problems facing YABER and proffered measures to improve their training needs in Nigeria.

The researchers used participants from Edo State, Abuja and Lagos State, Nigeria. This study adopted a qualitative research approach. The researchers accomplished saturation after 40 virtual interviews and adopted a thematic analysis for the primary data.

The research shows that the built environment research refines current and creates new knowledge. The built environment researchers (trainers and trainees) need training but face challenges. Findings clustered measures to improve quality research publications in the built environment through YABER training into government/regulatory agencies-related, higher education institutions-related and researcher-related measures.

The developed framework and thematic network analysis could be used to stimulate YABER training needs and, by extension, stir Nigeria’s higher education institutions regulatory agencies to upgrade requirements for academic staffers, especially published articles, to be compulsorily Scopus/Web of Sciences indexed for promotion exercise. This is the global best practice, and Nigerian scholars cannot be in isolation. It will form part of this study’s implication and revitalise UNSDG 4.

The penetration of mobile social media has given birth to various online collective spaces (OCSs) within cross-functional project teams (CFPTs), which have significantly transformed knowledge sharing (KS) practice. While existing literature has endeavored a lot on KS factors within CFPTs, our understanding of KS in OCSs is limited, thus constituting the central of the present study.

Centering on communication visibility, the core feature of KS in OCSs, this study combines social power theory and knowledge governance theory to shed light on the influence of two agents, i.e. members in the OCS and the project team. Data were collected by administering a questionnaire survey to 205 project team members in China. Ordinary least squares regression and fuzzy-set qualitative comparative analysis (QCA) techniques are used to analyze the data.

The ordinary least squares (OLS) regression results suggest that expert power of oneself, formal knowledge governance mechanism (KGM) and group size positively influence both KS quantity and quality. Besides, hierarchical distance is found to negatively influence KS quantity, and informal KGM is found to positively affect KS quality. The fuzzy-set QCA results reveal three configurations sufficient for KS quantity and four configurations sufficient for KS quality. Notably, the combination of expert power of oneself, formal and informal KGMs is essential for both KS quantity and quality.

This study provides valuable insights into KS in OCSs by synthesizing multi-level contextual antecedents from multiple theoretical perspectives. The results of OLS regression and fuzzy-set QCA are discussed, offering a comprehensive understanding of the mechanisms impacting KS. Ultimately, this study aims to offer guidance to managers on effectively facilitating KS within the contemporary digital era.

This study explores in-store retail sales practices for alternative protein products in Italy, with a focus on plant-based meat alternatives (PBMAs) compared to conventional meat products. It also investigates PBMA across different brand and business protein orientations to uncover disparities in retail practices, with attention to conventional and discount retailing.

Data are collected in Bologna, a mid-size metropolitan area in Italy, during autumn 2023. The methodology involved conducting in-person store audits across ten supermarkets and hypermarkets. The data collected encompasses variables such as protein type, product format, price, promotions, product shelf placement and protein orientation. Data elaboration includes Analysis of variance (ANOVA) testing and multivariate linear regression.

Results support that retail management practices price PBMA higher, offer fewer promotions and place them in the “ready-to-eat” department versus the meat department, if compared to conventional meat products. This suggests that Italian retailers do not consider PBMA as a direct alternative to the meat, but rather as a distinct food product category with its own retail management practices. The study also reveals that PBMA brand and business protein-orientation management practices influence pricing and sales. Retailers’ managerial approach shapes PBMA sales and consumer purchasing behavior.

The study is pioneering research on retailers and PBMA, a rapidly expanding food category. It focuses on Italy, a country where interest in alternative protein products remains limited but shows significant potential for growth. Finally, it provides a detailed analysis of in-store retail food management practices balancing PBMA with conventional meat products.

This study aims to determine how and through what mechanisms the outward foreign direct investment (OFDI) promotion effect of the Belt and Road initiative (BRI-OFDI) affects domestic investment. It is motivated by the context that China is fostering a new development pattern, as well as by the impetus from the Belt and Road initiative for the new pattern.

Drawing on data of Chinese-listed companies, this study uses a difference-in-difference method to explore the effect of the BRI-OFDI on domestic investment and a mediation model to illustrate the mechanisms.

The BRI-OFDI has a significantly positive effect on domestic investment, meaning that the Belt and Road initiative's OFDI promotion effect crowds in domestic investment. The results are heterogeneous: the crowding-in effect mainly exists in non-state-owned and technology-intensive enterprises, while a crowding-out effect is seen in state-owned and labor-intensive enterprises. The easing of corporate financing constraints and the expansion of market demand are two important mechanisms.

This study uses the Belt and Road initiative as an exogenous shock to investigate the impact of the initiative-induced OFDI promotion effect on domestic investment. It addresses the potential endogeneity issue confronting the studies on the relationship between OFDI and domestic investment in the literature. The authors focus on the possible spillover effects of the Belt and Road initiative discussing the impact of the BRI-OFDI on domestic investment from the micro-firm perspective. It offers a new perspective to objectively assess the initiative's policy effect.

The case portrays an actual organization, real people and an authentic marketing situation. Both primary and secondary data were used to develop the case. Interviews with the company’s founders were a major source of primary data. Email exchanges with the company’s leadership were used to verify and elucidate details within the case and instructor’s manual. Other primary data included direct observations of how maize was milled, sold in the marketplaces and cooked into various staple foods. Secondary data about the company were obtained from the company’s website, social media (Facebook, Twitter, Instagram) and articles in the press. Information on the company’s operating environment was derived from published government reports. The authors also drew on secondary data about the statistics, practices and issues involved in maize production and the agro-processing industry in Ghana.

This case features Sahel Grains Ltd, an agro-processing company based in Ghana, West Africa, striving to grow its maiden product, Faast Mmori. This ready-to-cook corn dough provides a more hygienic and convenient way of preparing local meals, compared to the traditional method, which involves taking maize grain to the local mill facilities and paying to have it milled before cooking. Alternatively, consumers purchase corn dough from the markets to make traditional meals. Since the company launched the product in Kumasi in 2018, sales have grown with the augmented street sales promotion and expanded distribution in premium supermarkets such as Shoprite and Citydia. However, starting in November 2020, the sales seemed to plateau with dwindling new customers, and the monthly dough sales in Kumasi dropped for the first time in December 2020. Although the sales regained positive growth, they then started to lose momentum.

In this scenario, Kofi, the CEO and co-founder, is considering marketing strategies to catalyze growth. Students assume the role of Kofi and are asked to recommend growth strategies to move the company forward. In doing so, they must scan the market environment and analyze the product’s market positioning. More importantly, they are challenged to develop strategies for managing growth.

This case is intended for undergraduate students in an introductory course in marketing, management, entrepreneurship and business in general. It introduces students to key marketing concepts, such as market environment scanning, positioning, product life cycle and market growth strategy.

The purpose of this study is to examine the narrowing of the gender publication gap (GPG) and predict when gender publication parity will be achieved. It investigates if women’s publication rates are catching up with men’s when the proportion of published articles by women will match their representation in the field, and how the gender gap and parity are changing concerning lead authorships. The study analyzes data from 11,097 researchers across 8 management journals from 2002 to 2020, revealing a higher growth rate in women’s publications and varying degrees of parity achievement between micro and macro domains.

We created a database of all researchers who published at least one article in eight management journals from January 2002 through December 2020. It included 11,097 unique researchers who produced 7,357 unique articles, resulting in 21,361 authorships. We used data from the Web of Science to identify articles and their authors, filtering for “articles” and “reviews” only. We used allometric modeling and time series analysis to examine the GPG and forecast gender publication parity.

We found that the GPG is narrowing, with women’s publication rates growing faster than men’s. Parity in lead authorships has already been achieved or is within reach for many journals, especially in micro domains. However, macro-oriented journals show slower progress, with some not expected to reach parity until 2045 or later. These improvements are linked to increased representation of women in leadership positions and targeted mentoring programs in micro domains.

While our study focused on publications, it did not account for citations, which could provide a more comprehensive view of research impact. Future research should explore other journals and different time windows and include citation analysis to understand the GPG and parity further.

The narrowing GPG is a positive development for organization studies, particularly in micro domains. This progress can mitigate stereotypes about women’s abilities, promote equity in hiring and promotion by considering authorship order and highlight the importance of targeted mentoring programs to reduce barriers for women. Additionally, business schools should identify and address performance situational constraints that disproportionately affect women, using techniques like the critical incidents approach to design effective interventions.

The study’s societal implications include fostering greater gender equity in academic publishing, which can influence broader social norms and reduce gender stereotypes in academia. Achieving gender parity in publications can lead to more equitable hiring, promotion and recognition practices. Additionally, it highlights the importance of removing performance situational constraints and biases that hinder women’s academic progress, thus promoting a more inclusive and fair academic environment. These changes can inspire other fields to implement similar measures, contributing to societal progress toward gender equality.

The study’s originality/value lies in its longitudinal approach to analyzing the GPG in organization studies, contrasting with prior cross-sectional studies. It provides new insights by predicting when gender parity will be achieved in various journals, showing faster progress in micro domains compared to macro domains. Additionally, the study introduces methodological innovations such as allometric modeling and scenario-based analyses, highlighting the importance of reducing situational constraints for women in academia. These findings offer a nuanced understanding of the ongoing efforts and challenges in achieving gender equity in academic publishing.

This study aims to deeply understand customer experiences toward Internet of Things (IoT) applications in retail by developing machine learning models for aspect-based sentiment analysis (SA). It includes creating a related terms dictionary and proposing implications for retail businesses in Vietnam based on these analyses. The ultimate goal is to gain insights into customer opinions and assist administrators in formulating effective digital transformation and business strategies within the Vietnamese market.

Initially, this research uses qualitative methods to identify different aspects of customer experience at stores equipped with IoT applications. Then, quantitative methods were applied through classification machine learning models which were trained on the annotated data set to classify comments into aspects and sentiments. Finally, the classification results were analyzed and visualized to draw implications about customer opinions of these stores.

This study collected 77,042 customers’ comment from potential and actual customers who have ever shopped at retail stores with IoT applications deployed worldwide, identified ten new aspects of customer experience in this field and built a dictionary of related terms. Furthermore, this study contributed two efficient ensemble models with an accuracy of 81% and 89% for analyzing aspects and customer sentiments, respectively. This study also proposes implications for managers regarding the use of IoT technology in retail stores to improve shopping experiences for customers.

This study’s findings help managers develop appropriate digital transformation and business strategies for integrating IoT technology into retail stores, especially for retail businesses in the Vietnamese market based on the analysis results and proposed model.