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This paper aims to provide researchers and practitioners with a consumer-focused alternative for considering the integration of artificial intelligence (AI) into services.

The paper reviews and critiques the most popular frameworks for addressing AI in service. It offers an alternative approach, one grounded in social psychology and leveraging influential concepts from management and human–computer interaction.

The frameworks that dominate discourse on this topic (e.g. Huang and Rust, 2018) are fixated on assessing technology-determined feasibility rather than consumer-granted permissibility (CGP). Proposed is an alternative framework consisting of three barriers to CGP (experiential, motivational and definitional) and three responses (communicate, motivate and recreate).

The implication of this research is that consistent with most modern marketing thought, researchers and practitioners should approach service design from the perspective of customer experience, and that the exercise of classifying service occupation tasks in terms of questionably conceived AI intelligences should be avoided.

Indicative of originality, this paper offers an approach to considering AI in services that is nearly the polar opposite of that widely advocated by e.g., Huang et al., (2019); Huang and Rust (2018, 2021a, 2021b, 2022b). Indicative of value is that their highly cited paradigm is optimized for predicting the rate at which AI will take over service tasks/occupations, a niche topic compared to the mainstream challenge of integrating AI into service offerings.

1. Understand how the corporate lifecycle could trigger a necessity of making a tough decision to develop new business ventures based on the corporate lifecycle theory; and how changes in the external environment could hasten such a decision.

2. Analyze how a company can leverage its internal organizational structure to share and utilize cross-departmental resources and capabilities to support new venture businesses according to the synergy effect perspective.

3. Undertake a resource-based view analysis to evaluate the external and internal resources needed for corporate new venture development.

4. Identify the best course of action for the decision-maker by comparing, contrasting, applying and evaluating the two different models of corporate new venture development in the e-commerce business: the centralized organizational model and the decentralized organizational model and evaluate the pros and cons associated with each mode in the context of Dahan’s external and internal environments.

Since its inception in 2003, Dahan’s traditional business in SMS (Short Message Services) and data had gained thousands of customers across China and won top rankings in the industry. Despite its achievements, Dahan encountered difficulties when it entered the new e-commerce market, as the domain knowledge about the new business was very different from the domain knowledge in its traditional business. Furthermore, the emerging B2B e-commerce industry was very different from the traditional business in that the former mainly targeted corporate clients and the latter targeted individual customers in the B2C industry. This case examined the critical decisions that Xiaofen Huang, the CEO of Dahan E-Commerce Corporation and Co-Founder of Dahan Tricom Group, had to make and external, especially Internal, resources the Dahan Group needed in developing its new venture.

Specifically, this case explored how Huang would go through the mental process to make the best possible decision to help the company not only to survive, but also thrive in the rapidly-changing and competitive digital environment: it urgently needed to finalize an organizational incubation model to support the further development of its e-commerce and future new venture activities with two options to choose from: the centralized organizational model or the decentralized organizational model. A key challenge facing Huang was to decide which option was best suited to motivate salespeople in different departments to help one another, especially in the new B2B e-commerce business and to grow that new business.

In the case, Dahan’s growth aspirations and its motivation to transform its traditional business into a new e-commerce business were discussed. Second, when external challenges were examined, how Dahan explored the B2B e-commerce business using a trial-and-error learning process was explained. Third, when internal challenges were examined, how Dahan incubated its new B2B e-commerce business and its practices for leveraging and sharing resources/capabilities, as well as cross-departmental and cross-divisional collaboration through a resource-based lens, were illustrated. Last, the most critical learning in the case presented an immediate decision-making dilemma on which organizational incubation models to choose from for further new business development, where students learn to analyze both external and internal factors and consider Dahan’s available resource and founder’s aspiration, available strategic options to derive a best possible decision to suit the stage of the company’s lifecycle and founders’ vision.

This case was designed for use in undergraduate courses on corporate innovation, new venture development, corporate innovation, corporate entrepreneurship, e-commerce and growth.

Teaching notes are available for educators only.

CSS 11: Strategy.

The purpose of this paper is to explore how internal and external factors simultaneously drive firms to adopt green supply chain (GSC) initiatives and to construct a comprehensive research model by drawing upon institutional theory, stewardship theory, and view of performance.

The data collected from 380 manufacturers in the electrical and electronics industries in Taiwan were analyzed via structural equation modeling and bootstrapping.

First, institutional pressures affect the GSC initiatives of firms. Second, institutional pressures influence the environmental stewardship behaviors (ESBs) of managers. Third, the ESBs of managers affect the GSC initiatives of firms. Fourth, the GSC initiatives of firms influence their environmental performance, economic performance, and competitiveness. Fifth, the bootstrapping results reveal that institutional pressures indirectly affect the GSC initiatives of firms through the ESBs of managers.

Environmental sustainability has intensified the need for firms to develop a corporate culture. Future research can investigate the relationship among the institutional pressures, greening corporate culture, and GSC initiatives of firms.

Those managers facing institutional pressures must continually focus on the effects of external factors on the GSC initiatives of their firms. They must also increase their commitment and support to such initiatives to attain favorable levels of environmental performance, economic performance, and competitiveness.

This study integrates four streams of literature on institutional theory, stewardship theory, GSC initiatives, and view of performance. Apart from analyzing field- and organization-level data simultaneously, this paper is also the first to demonstrate the relationships among institutional pressures, ESBs of managers, GSC initiatives, and firm performance.

Integrating economic and green initiatives into firm strategies is a challenge for firms in various industries. The study aims to incorporate multiple views, i.e. green innovation theory (GIT), the green institutional perspective (GIP) and the natural-resource-based view (NRBV), to develop a comprehensive model to explore why and how firms implement green product innovation (GPI).

The study explores the relationships among institutional pressure, the firm's green resources and GPI. The research also distinguishes two different types of GPI: exploratory GPI and exploitative GPI. A total of 270 valid questionnaires were collected from electrical and electronics manufacturers in Taiwan. The authors employed structural equation modeling (SEM) using analysis of moment structures (AMOS) 23.0 to test the hypotheses.

The results show that institutional pressure has a significant positive correlation with the firm's green resources. Furthermore, institutional pressure has a significantly positive influence on exploratory GPI and exploitative GPI, respectively. The firm's green resources also have a significantly positive effect on both exploratory GPI and exploitative GPI. In addition, institutional pressures have significantly positive indirect effect on both exploratory GPI and exploitative GPI.

Economic benefits and environmental sustainability are the most pressing issues faced by the electrical and electronics industry today. The study's investigation covers Taiwanese electrical and electronics manufacturers only, so the test of the research model has limited generalizability. The authors suggest that to expand the generalizability of the findings, future research should examine this model in the context of other regions such as Southeast Asia, Africa, South America, etc.

The study has many interesting implications for both practitioners and policymakers. The authors' findings suggest that while Taiwanese electrical and electronics manufacturers face significant pressure from customers, competitors and regulation requirements (e.g. waste electrical and electronic equipment [WEEE], restriction of hazardous substances [RoHS] and energy using product [EuP] directives), firms in that sector should efficiently and effectively deploy their green resources and then perform proper GPI (e.g. exploratory GPI or exploitative GPI). These results also serve as a reminder to policymakers that balancing coercive (command-and-control) mechanisms with incentives and voluntary mechanisms is the best means by which to develop motivational and effective GPI policies.

First and foremost, the paper divides GPI into exploratory GPI and exploitative GPI. Furthermore, the research incorporates two important schools of thought, i.e. the GIP and NRBV, thus providing a more holistic view by which to explore why and how companies adopt GPI.

Applying the institution-based view and the resource-based view, this study explores how state ownership influences early internationalization of emerging market firms, how it interacts with firm size to have an impact and how the proportion of SOEs moderates this interaction effect.

Based on a sample of 717 Chinese listed firms, this study uses Poisson regression, ordinary least square regression and Heckman two-stage estimation to analyze the data.

This study finds state ownership does not influence early internationalization, state ownership and firm size jointly can have a significant impact, and the proportion of SOEs in an industry sector can moderate this interaction effect.

This study enriches our understanding of the impact of home government involvement on internationalization strategies of emerging market firms, contributes to early internationalization research by building the theoretical mechanisms about these direct and interaction effects and by providing empirical results and provides important advices to firm decision-makers and government policymakers. By examining these interaction effects, it also provides a solution to the theoretical conflict created by the two opposing effects of state ownership.

Prior research on green innovation has shown that institutional pressure stimulates enterprises to adopt green innovation. However, an institutional perspective does not explain why firms that face the same amount of institutional pressure execute different environmental practices and innovations. To address this research gap, the authors linked institutional theory with upper echelons theory and organization performance to build a comprehensive research model.

A total of 800 questionnaires were issued. The final usable questionnaires were 195, yielding a response rate of 24.38%. AMOS 23.0 was used to analyze the data and examine the relationships between the constructs in our model.

Institutional pressures affected both green innovation adoption (GIA) and the top management team's (TMT's) response. TMT's response influenced GIA. GIA was an important factor affecting firm performance. Furthermore, TMT's response mediated the relationship between institutional pressure and GIA. Institutional pressures indirectly affected green innovation performance but did not influence economic performance through GIA. Finally, TMT's response indirectly impacted firm performance through GIA.

The authors draw on institutional theory, upper echelons theory, and a performance-oriented perspective to explore the antecedents and consequences of GIA. This study has interesting implications for leaders and managers looking to implement green innovation and leverage it for firm performance to out compete with market rivals as well as to make the changes in collaboration with many other companies including market rivals to gain success in green innovation.

Online games are widely adopted electronic applications that facilitate flow experiences, which is a highly enjoyable experience for players, thus motivating further engagement in online gameplay. During gameplay, players set gaming goals, and they must make cognitive efforts to achieve these goals. However, we do not know how goal-setting and cognitive gaming elements (game complexity and game familiarity) create flow, indicating a research gap. To fill this gap, we use the cognitive gaming elements in the literature and the theoretical elements of goal-setting theory to build a model.

Conducting a large-scale online survey, we collect 3,491 responses from online game players and use structural equation modeling for data analysis.

We find that challenging goals, game complexity, game familiarity and telepresence are positively linked to player-perceived flow, explaining 45% of the variance. The new finding is that challenging goals can strengthen the link between game complexity and flow. We also find that telepresence can strengthen the link between game familiarity and flow.

Our study provides the novel insight that gaming goals and cognitive gaming elements can generate player-perceived flow. This insight can help game makers design gaming elements to accommodate players' cognitive efforts to achieve in-game goals, thus creating flow and effectively increasing players' game engagement.

We theorize the critical role of angel investors' affective experiences and first impressions in the context of entrepreneurial finance. We develop a model and propositions to illustrate why angel investors make the decision to continue screening, thus explaining why certain investment proposals make it, while others do not.

Drawing on affective events theory and the literature on affective experiences, we theorize how the perceptions of pitches that trigger positive or/and negative physiological arousal, short-lived emotions, and associated thoughts are different, thus allowing us to build new theory of how these different experiences can influence the outcome of the evaluation process in the initial screening stage.

Our model suggests that the initial evaluation unfolds in five stages: perception of an entrepreneurial pitch, physiological arousal, emotions, first impression, and a decision to continue screening. When different manifestations of physiological arousal and subsequent emotions set the tone of first impressions, they can be either a positive, negative, or mixed experience. While positive and mixed first impression can lead to selection, negative first impression can lead to rejection.

We illustrate what is of value for angel investors when they look for new investments, and why certain entrepreneurial pitches lead to the decision to continue screening, while others do not. We propose that what angel investors feel is particularly important in situations where they are not yet making the ultimate decision to invest money but are involved in decisions about whether to continue to spend time to investigate the investment proposal.

This study aims to provide insights into Airbnb’s exit from the China market, specifically from the perspective of platform competition.

Based on the understanding of the evolution and competition of peer-to-peer (P2P) accommodation market in China and the double-edged network effects, this viewpoint article provides an in-depth discussion on Airbnb’s withdrawal from the China market.

This viewpoint paper contends that Airbnb faced increasing challenges in establishing unique competitive advantages against local rivals, who demonstrate a capacity for innovation and maintaining loyal customers in adapting to the market evolution. Consequently, this may inhibit Airbnb from attracting the mainstream market and lead Airbnb into a negative spiral, exacerbated by indirect network effects.

This study offers insights into the failure of an internationalisation process, drawing from an analysis of the competitive environment and the competition strategies of P2P accommodation platforms in China. These findings have practical implications for the implementation of international business strategies in P2P accommodation.

本观点文章旨在基于平台竞争的视角对爱彼迎退出中国的现象进行阐释

基于对中国共享住宿/民宿市场的演变和竞争、双边网络效应的理解, 本文对爱彼迎退出中国进行了深入探讨。

本文提出, 爱彼迎在建立独特竞争优势以应对本地竞争对手方面面临日益严峻的挑战, 因为本地竞争者在适应市场变化方面展现出突出的创新和留客的能力。这可能会阻碍爱彼迎吸引主流市场, 并导致其跌入由间接网络效应加剧的恶性循环中。

基于对中国共享住宿平台的竞争环境和策略的分析, 本文洞悉了一个国际化失败的案例。本文的发现对于共享住宿的国际化策略实施具有实践意义。

Este artículo de opinión pretende aportar ideas sobre la salida de Airbnb del mercado chino, concretamente desde la perspectiva de la competencia entre plataformas.

Basándonos en la comprensión de la evolución y la competencia del mercado de alojamientos P2P en China, así como en los “efectos de red de doble filo”, este artículo de opinión ofrece una discusión en profundidad sobre la retirada de Airbnb del mercado chino.

Este documento sostiene que Airbnb enfrentó desafíos crecientes para establecer ventajas competitivas únicas frente a sus rivales locales, demostrando estos últimos una capacidad de innovación y del mantenimiento de la lealtad de sus clientes al adaptarse a la evolución del mercado. En consecuencia, esto puede inhibir a Airbnb para atraer al mercado principal y llevar a la empresa a una espiral negativa, exacerbada por efectos de red indirectos.

Este estudio ofrece una visión del fracaso de un proceso de internacionalización, a partir de un análisis del entorno competitivo y de las estrategias de competencia de las plataformas de alojamiento P2P en China. Estos resultados tienen implicaciones prácticas para la aplicación de estrategias empresariales internacionales en los alojamientos P2P.

This paper aims to provide a predictive framework of customer churn through six stages for accurate prediction and preventing customer churn in the field of business.

The six stages are as follows: first, collection of customer behavioral data and preparation of the data; second, the formation of derived variables and selection of influential variables, using a method of discriminant analysis; third, selection of training and testing data and reviewing their proportion; fourth, the development of prediction models using simple, bagging and boosting versions of supervised machine learning; fifth, comparison of churn prediction models based on different versions of machine-learning methods and selected variables; and sixth, providing appropriate strategies based on the proposed model.

According to the results, five variables, the number of items, reception of returned items, the discount, the distribution time and the prize beside the recency, frequency and monetary (RFM) variables (RFMITSDP), were chosen as the best predictor variables. The proposed model with accuracy of 97.92 per cent, in comparison to RFM, had much better performance in churn prediction and among the supervised machine learning methods, artificial neural network (ANN) had the highest accuracy, and decision trees (DT) was the least accurate one. The results show the substantially superiority of boosting versions in prediction compared with simple and bagging models.

The period of the available data was limited to two years. The research data were limited to only one grocery store whereby it may not be applicable to other industries; therefore, generalizing the results to other business centers should be used with caution.

Business owners must try to enforce a clear rule to provide a prize for a certain number of purchased items. Of course, the prize can be something other than the purchased item. Business owners must accept the items returned by the customers for any reasons, and the conditions for accepting returned items and the deadline for accepting the returned items must be clearly communicated to the customers. Store owners must consider a discount for a certain amount of purchase from the store. They have to use an exponential rule to increase the discount when the amount of purchase is increased to encourage customers for more purchase. The managers of large stores must try to quickly deliver the ordered items, and they should use equipped and new transporting vehicles and skilled and friendly workforce for delivering the items. It is recommended that the types of services, the rules for prizes, the discount, the rules for accepting the returned items and the method of distributing the items must be prepared and shown in the store for all the customers to see. The special services and reward rules of the store must be communicated to the customers using new media such as social networks. To predict the customer behaviors based on the data, the future researchers should use the boosting method because it increases efficiency and accuracy of prediction. It is recommended that for predicting the customer behaviors, particularly their churning status, the ANN method be used. To extract and select the important and effective variables influencing customer behaviors, the discriminant analysis method can be used which is a very accurate and powerful method for predicting the classes of the customers.

The current study tries to fill this gap by considering five basic and important variables besides RFM in stores, i.e. prize, discount, accepting returns, delay in distribution and the number of items, so that the business owners can understand the role services such as prizes, discount, distribution and accepting returns play in retraining the customers and preventing them from churning. Another innovation of the current study is the comparison of machine-learning methods with their boosting and bagging versions, especially considering the fact that previous studies do not consider the bagging method. The other reason for the study is the conflicting results regarding the superiority of machine-learning methods in a more accurate prediction of customer behaviors, including churning. For example, some studies introduce ANN (Huang et al., 2010; Hung and Wang, 2004; Keramati et al., 2014; Runge et al., 2014), some introduce support vector machine ( Guo-en and Wei-dong, 2008; Vafeiadis et al., 2015; Yu et al., 2011) and some introduce DT (Freund and Schapire, 1996; Qureshi et al., 2013; Umayaparvathi and Iyakutti, 2012) as the best predictor, confusing the users of the results of these studies regarding the best prediction method. The current study identifies the best prediction method specifically in the field of store businesses for researchers and the owners. Moreover, another innovation of the current study is using discriminant analysis for selecting and filtering variables which are important and effective in predicting churners and non-churners, which is not used in previous studies. Therefore, the current study is unique considering the used variables, the method of comparing their accuracy and the method of selecting effective variables.