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Today’s in-demand skills may not be needed tomorrow. As companies are adopting a new group of technologies, they are in huge need of information technology (IT) professionals who can fill various IT positions with a mixture of technical and problem-solving skills. This study aims to adopt a sematic analysis approach to explore how the US Information Systems (IS) programs meet the challenges of emerging IT topics.

This study considers the application of a hybrid semantic analysis approach to the analysis of IS higher education programs in the USA. It proposes a semantic analysis framework and a semantic analysis algorithm to analyze and evaluate the context of the IS programs. To be more specific, the study uses digital transformation as a case study to examine the readiness of the IS programs in the USA to meet the challenges of digital transformation. First, this study developed a knowledge pool of 15 principles and 98 keywords from an extensive literature review on digital transformation. Second, this study collects 4,093 IS courses from 315 IS programs in the USA and 493,216 scientific publication records from the Web of Science Core Collection.

Using the knowledge pool and two collected data sets, the semantic analysis algorithm was implemented to compute a semantic similarity score (DxScore) between an IS course’s context and digital transformation. To present the credibility of the research results of this paper, the state ranking using the similarity scores and the state employment ranking were compared. The research results can be used by IS educators in the future in the process of updating the IS curricula. Regarding IT professionals in the industry, the results can provide insights into the training of their current/future employees.

This study explores the status of the IS programs in the USA by proposing a semantic analysis framework, using digital transformation as a case study to illustrate the application of the proposed semantic analysis framework, and developing a knowledge pool, a corpus and a course information collection.

The purpose of this study is to investigate the key predictors and outcomes of task–technology fit (TTF) of facial recognition payment systems with the moderating role of cultural differences in the restaurant industry.

The survey responses were collected from 336 South Korean and 336 US restaurant customers.

The results revealed that function significantly affected TTF in both groups. Unique to the Korean sample, emotion was found to be a significant determinant of TTF, whereas convenience and social influence were key predictors of TTF only for the US sample. TTF had significant and positive effects on the three dimensions of behavioral intentions in both groups. The result of multi-group analysis showed that cultural differences moderated the effect of convenience on TTF and the effect of emotion on TTF.

The authors provided recommendations for restaurant operators and technology companies seeking to improve customer TTF and acceptance of facial recognition payment systems for the first time.

本研究旨在调查面部识别支付系统任务技术匹配（TTF）的关键前置因素和影响, 以文化差异为调节变量, 研究其在餐饮行业的应用。

我们收集了来自336名韩国和336名美国餐厅顾客的调查回答。

结果显示, 在两组中, 功能显著影响TTF。对于韩国样本来说, 情感被发现是TTF的重要决定因素, 而对于美国样本来说, 方便性和社会影响是TTF的关键预测因素。在两组中, TTF对行为意向的三个维度均产生了显著且积极的影响。多组分析结果显示, 文化差异在方便性对TTF的影响以及情感对TTF的影响中起到了调节作用。

我们首次为寻求改善顾客TTF和接受面部识别支付系统的餐厅经营者和技术公司提供了建议。

Structural equation modeling (SEM) is a well-established and frequently applied method in various disciplines. New methods in the context of SEM are being introduced in an ongoing manner. Since formal proof of statistical properties is difficult or impossible, new methods are frequently justified using Monte Carlo simulations. For SEM with covariance-based estimators, several tools are available to perform Monte Carlo simulations. Moreover, several guidelines on how to conduct a Monte Carlo simulation for SEM with these tools have been introduced. In contrast, software to estimate structural equation models with variance-based estimators such as partial least squares path modeling (PLS-PM) is limited.

As a remedy, the R package cSEM which allows researchers to estimate structural equation models and to perform Monte Carlo simulations for SEM with variance-based estimators has been introduced. This manuscript provides guidelines on how to conduct a Monte Carlo simulation for SEM with variance-based estimators using the R packages cSEM and cSEM.DGP.

The author introduces and recommends a six-step procedure to be followed in conducting each Monte Carlo simulation.

For each of the steps, common design patterns are given. Moreover, these guidelines are illustrated by an example Monte Carlo simulation with ready-to-use R code showing that PLS-PM needs the constructs to be embedded in a nomological net to yield valuable results.

Relationships are a critical success factor for business operations across markets with dominant Chinese culture, like Taiwan. The intersection of a high-quality institutional environment and a traditional Chinese cultural background in Taiwan provides a unique setting for exploring different types of relational mechanisms and ensuing renqing practices (i.e. reciprocal exchange of favors with empathy). The purpose of this paper is to examine when, where and how Taiwanese high-performance organizations manage and deploy interorganizational renqing across their business relationship portfolios. Answering these questions can help build a theory of interorganizational renqing and advance interorganizational reciprocity theorization more generally.

This research is motivated by two key research questions. First is related to how renqing givers understand renqing in the context of their organizations and their interorganizational business relationship portfolios. Second, whether organizations prefer a neutral renqing balance, a renqing debt or a renqing surplus is another point of interest. The study is based on interviews with upper echelon elite informants at six high-performing Taiwanese organizations with business relationship portfolios worldwide.

It is found that interorganizational renqing is deployed as a hybrid resource, taking on the functions of both an investment and a type of insurance against risk. Two notable differences between interorganizational and interpersonal renqing are also noted. First, the social exchange norm aspect of renqing points to salient social exchange norms also in interorganizational exchanges. This confirms the importance of understanding not only the regulative and normative dimensions of business relationships, as a type of institution, but also the cognitive dimensions and underlying institutional logics. Second, this study shows that unlike at the interpersonal level, the notion of renqing debt is not common at the interorganizational level – at least not within high-performance organizations with market leader positions.

This study explores interorganizational renqing practices and their strategic deployment through the use of “accessing” and “embedding” relational mechanisms. The study also adds to the poorly understood nature of interorganizational reciprocity and provides support for developing a theory of interorganizational renqing, as a form of interorganizational reciprocity within a Chinese cultural context.

Generalized structured component analysis (GSCA) and partial least squares path modeling (PLSPM) are two key component-based approaches to structural equation modeling that facilitate the analysis of theoretically established models in terms of both explanation and prediction. This study aims to offer a comparative evaluation of GSCA and PLSPM in a predictive modeling framework.

A simulation study compares the predictive performance of GSCA and PLSPM under various simulation conditions and different prediction types of correctly specified and misspecified models.

The results suggest that GSCA with reflective composite indicators (GSCA_R) is the most versatile approach. For observed prediction, which uses the component scores to generate prediction for the indicators, GSCA_R performs slightly better than PLSPM with mode A. For operative prediction, which considers all parameter estimates to generate predictions, both methods perform equally well. GSCA with formative composite indicators and PLSPM with mode B generally lag behind the other methods.

Future research may further assess the methods’ prediction precision, considering more experimental factors with a wider range of levels, including more extreme ones.

When prediction is the primary study aim, researchers should generally revert to GSCA_R, considering its performance for observed and operative prediction together.

This research is the first to compare the relative efficacy of GSCA and PLSPM in terms of predictive power.

Traditional Korean buildings do not differ significantly in form or structural style according to era or building type. The authors interpret this from a generative rather than a typological perspective. The generation perspective considers factors forming the buildings and is connected to the prevailing thoughts of the era.

This study analyzes the generation method of seowon facilities in the Joseon Dynasty (1392–1897), focusing on the Dosan Seowon. Based on Koreans' long-term thinking, the authors applied the extracted architectural space generation layers for analysis, and present an integrated method of generation layers when the Dosan Seowon was built.

The immanent, physical and body perceptual layers presented for seowon formation analysis are represented by thought, form and territory. Specific aspects of these layers in the Dosan Seowon are analyzed, including the architectural arrangement that connects the land conditions with neo-Confucian courtesy and order, the collective architectural form considering the energy of yin and yang, and the elements of objects that affect the human body perception. This form of architecture was closely linked with and strongly influenced by monistic philosophy.

After the Korean War, architects judged traditional buildings only by shapes, and quickly accepted Western architecture's forms. Presenting a generative perspective of traditional Korean architecture expands the theoretical research direction of modern succession.

This is the first attempt to examine the generation method based on the Dosan Seowon's generation layers.

The purpose of this study examined the effect of the eight dimensions of consumer innovativeness on brand satisfaction. In addition, this study investigated how brand satisfaction affects brand preference and brand loyalty. Lastly, how brand preference plays to form brand loyalty was also explored.

A survey was conducted via an online platform with the participants using an online firm in South Korea to evaluate the proposed research model. The data was collected from 326 people who used a coffee shop where robots provide the services.

The data analysis results indicated that the five dimensions of consumer innovativeness, which include novelty seeking, openness, quality experience seeking, hedonic experience seeking and social distinctiveness, aid to enhance brand satisfaction. Furthermore, it was discovered that brand satisfaction plays an important role with the formation of brand preference and brand loyalty.

There are few studies which focus how coffee consumers assess the value of a coffee brand. Thus, it would be meaningful to examine what impacts of consumer innovativeness exist in regards to robotic barista services that are related to brand satisfaction, brand preference and brand loyalty.

本研究考察了消费者创新性的八个维度对品牌满意度的影响。此外, 本研究还调查了品牌满意度如何影响品牌偏好和品牌忠诚度。最后, 还探讨了品牌偏好在形成品牌忠诚度方面的作用。

本研究通过在线平台在韩国进行了一项调查, 参与者使用一家提供机器人服务的咖啡店进行评估。数据收集自326名在该咖啡店使用服务的顾客。

数据分析结果表明, 包括新奇寻求、开放性、品质体验寻求、享乐体验寻求和社交独特性在内的五个消费者创新性维度有助于提高品牌满意度。此外, 品牌满意度在品牌偏好和品牌忠诚度的形成中起着重要作用。

目前很少有研究关注咖啡消费者如何评估咖啡品牌的价值。因此, 对于与品牌满意度、品牌偏好和品牌忠诚度相关的机器人咖啡师服务消费者创新性影响的研究具有重要意义。

Informal learning networks are critical to response to calls for practitioners to reskill and upskill in off-site construction projects. With the transition to the coronavirus disease 2019 (COVID-19) pandemic, social media-enabled online knowledge communities play an increasingly important role in acquiring and disseminating off-site construction knowledge. Proximity has been identified as a key factor in facilitating interactive learning, yet which type of proximity is effective in promoting online and offline knowledge exchange remains unclear. This study takes a relational view to explore the proximity-related antecedents of online and offline learning networks in off-site construction projects, while also examining the subtle differences in the networks' structural patterns.

Five types of proximity (physical, organizational, social, cognitive and personal) between projects members are conceptualized in the theoretical model. Drawing on social foci theory and homophily theory, the research hypotheses are proposed. To test these hypotheses, empirical case studies were conducted on two off-site construction projects during the COVID-19 pandemic. Valid relational data provided by 99 and 145 project members were collected using semi-structured interviews and sociometric questionnaires. Subsequently, multivariate exponential random graph models were developed.

The results show a discrepancy arise in the structural patterns between online and offline learning networks. Offline learning is found to be more strongly influenced by proximity factors than online learning. Specifically, physical, organizational and social proximity are found to be significant predictors of offline knowledge exchange. Cognitive proximity has a negative relationship with offline knowledge exchange but is positively related to online knowledge exchange. Regarding personal proximity, the study found that the homophily effect of hierarchical status merely emerges in offline learning networks. Online knowledge communities amplify the receiver effect of tenure. Furthermore, there appears to be a complementary relationship between online and offline learning networks.

Proximity offers a novel relational perspective for understanding the formation of knowledge exchange connections. This study enriches the literature on informal learning within project teams by revealing how different types of proximity shape learning networks across different channels in off-site construction projects.

Entrepreneurs and individual sellers heavily leverage their social ties embedded in social media, expressive or instrumental, to penetrate the market and achieve business success. However, the extant social commerce literature offers limited understanding on how different forms of buyer−seller social ties embedded in social media affect buyers' purchase behaviors. The study draws on the theoretical lens of social ties and proposes an integrative theoretical framework to understand the direct and indirect influences of expressive and instrumental ties (ExTSM and InTSM) between buyers and sellers on buyers' purchase intention (PI) in social commerce.

The authors first validated the measures of ExTSM and InTSM with survey data from 166 Weibo commerce buyers. They then tested their theoretical framework and hypotheses with survey data from 246 buyer−seller dyads in WeChat commerce.

With a buyer-centric view, (1) ExTSM and InTSM, respectively, had a direct negative and a positive influence on PI; (2) both trust and perceived product value displayed inconsistent mediation effects on the negative relationship between ExTSM and PI; and (3) only perceived product value mediated the positive influence of InTSM on PI. From sellers' viewpoint, (1) their ExTSM and InTSM with buyers were mixed up, and (2) the mingled social ties negatively impacted buyers' purchase intention.

The findings of the study advance the theoretical understanding of social commerce and offer practical guidance for small and medium-sized enterprises to effectively utilize social media for business purposes.

This study aims to follow a rigorous approach to identify, critically analyze and synthesize 75 papers published from 2000 to 2022.

The study presents a systematic literature review on identity expressiveness (IE), clarifying and expanding what is currently known about the concept.

To synthesize current knowledge on IE, the study uses the overarching framework of antecedents-phenomenon-consequences, using this same framework to identify gaps and future research directions. The findings show individual and brand-related factors such as the need for uniqueness and anthropomorphism as antecedents of IE, and eWOM/WOM, impulse purchases and upgrading to more exclusive lines as consequences of IE.

The study contributes to theory by synthesizing and mapping current understanding of the state of knowledge on the concept of IE while highlighting gaps in the extant literature and paving future research directions for scholars in the field.

The study offers useful insights for practitioners, broadening marketers’ actionable options in identity-based marketing. Marketers can use insights from this study to inform marketing strategy and communication campaigns for different types of brands.

To the best of the authors’ knowledge, this study is the first of its kind and offers an integrative review of the current literature on IE, thus enhancing understanding of the concept, its antecedents and consequences. The study also contributes to knowledge by highlighting future research priorities for researchers in this field of enquiry.