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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 paper is to provide an overview and analysis of current legislation and various schemes and practices that are available to employers and employees in relation to work life balance, family friendly work arrangements, leave entitlements and diverse modes of flexible work in Ireland. Focuses in particular on the Library and Information sector.

Introduces the concept of flexible working, followed by a review of relevant literature. Outlines what flexible work practices are, giving details of various types of flexible working, both statutory and non‐statutory (in Ireland). Then, discusses why flexible work practices have emerged and details background legislation and the issues that the introduction of flexible working raises. Draws conclusions about best practice in relation to the management of flexible work practices.

It is argued that commitment to work life balance is now firmly in the mainstream and is part of the political agenda in Ireland and the rest of the developed world. Flexibility in work practice is becoming an integral part of employment, particularly in public sector organisations, which are in effect, leading the way on this issue. Flexible work practices have many advantages for both employees and employers. They also create challenges, especially in terms of management. It is important to balance the requirements of the organisation with those of the employees. Key factors in the successful implementation of flexible working are training and communication.

The article provides a firm basis for further investigation and discussion.

This study aims to examine the differences among memorable brand experience, brand preference and behavioral intentions based on the type of service providers, such as robot servers and human servers. In addition, this study investigated the relationships among the four concepts.

The data was collected from 296 customers who experienced robot servers and from 307 customers who experienced human servers.

The data analysis results indicated that there was a statistical difference with the mean value of the five concepts according to the type of employee. The results also revealed that memorable brand experience has a positive influence on brand preference, which in turn positively influences intentions to use, word-of-mouth and willingness to pay more.

This study attempted to find the difference between robot servers and human servers in memorable brand experience, brand preference and behavioral intentions in the restaurant industry for the first time.

本研究旨在根据服务提供商的类型（例如机器人服务员和人工服务员）检查令人难忘的品牌体验、品牌偏好和行为意图之间的差异。 此外, 本研究调查了四个概念之间的关系。

数据收集自 296 名体验过机器人服务器的客户和 307 名体验过人工服务器的客户。

数据分析结果表明, 根据员工类型, 五个概念的平均值存在统计差异。 结果还表明, 难忘的品牌体验对品牌偏好有积极影响, 进而对使用意向、口碑和支付更多的意愿产生积极影响。

这项研究首次试图找出机器人服务员和人工服务员在餐饮业令人难忘的品牌体验、品牌偏好和行为意图方面的差异。

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。

This paper aims to figure out the relationship between energy consumption flow from a new perspective of embodied energy inventory index (EEII) and regional economic growth.

The input-output approach has been applied to calculate embodied energy inventory (EEI) and EEII using the data of 25 economies. Meanwhile, cluster analysis and panel data modeling were applied to carry out detailed research.

The results of cluster analysis show that there is a roughly negative relationship between EEII and gross domestic product (GDP) per capita, although there are some exceptions, such as Russia and Taiwan (Province of China). Panel data model results provide further evidence that there is a negative relationship between EEII and GDP per capita. Population is an important productive factor in the regional economic development. The study showed a positive relationship between EEII and population. Therefore, energy consumption flow is closely related to regional economic development.

The value of this paper is to use EEI and EEII to comprehensively clarify the energy consumption flow. The advantage of EEII is that it can reflect the energy embodied in fixed assets and infrastructure.

The purpose of this paper is to explore the relationship between social capital and collective action at the county level in the US while incorporating the moderating effects of community racial diversity and urbanity and to find the changing effects of social capital on philanthropic collective action for community education.

This paper employs a quantitative research design. The dependent variable measures philanthropic collective action for community education while the independent variable for social capital is measured as a community level index. Moderating variables include a community racial diversity index and urbanity. This analysis tests and interprets interaction effects using moderated multiple regression (MMR), with the baselines of MMR being grounded to multivariate ordinary least squares (OLS) regression. Analyses are carried out in the context of the USA during 2006 and 2010, with US counties employed as the unit of analysis.

The effects of social capital on philanthropic contributions decline in counties with low- and mid-levels of racial diversity. On the contrary, the effects of social capital increase in highly racially diverse counties. The three-way interaction model result suggests that racial diversity positively moderates social capital on philanthropic collective action for community education where the effect of social capital is strong and positive in highly racially diverse urban communities.

This research complicates the notion that social capital and racial diversity are negatively associated when exploring collective action and community education, and suggests effects of social capital varies with moderating effects on philanthropic collective action for community education.

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.

The literature revealed a limited number of studies on critical success factors (CSFs) in Saudi Arabia. These studies were either outdated, covered limited factors or focused on very specific issues of a project. In response to this knowledge gap, the purpose of this paper is to identify and assess the factors which affect the success of construction projects in Saudi Arabia.

In all, 91 CSFs were identified from the literature, and grouped under eight categories according to categorization schemes adopted by earlier studies and common characteristics shared by the factors. A questionnaire survey was adopted since it permits the collection of large volumes of data in a short period. In total, 61 responses from industry experts were used to compute the significance index for each factor and rank the most CSFs.

Contractors viewed the three most significant CSFs as “competency and capability of the contractors’ key personnel in different disciplines,” “adequacy of labor resources and their skills” and “the impact of the project on the public.” Consultants viewed the three most significant CSFs as “competency and capability of the consultants’ key personnel in different disciplines,” “clear communication channels between the owner/PM and the designer” and “PM competency, authority and involvement.”

Although a significant number of studies have investigated CSFs for construction projects, these studies do not provide an extensive list of CSFs, and none have studied CSFs in large-scale construction projects in Saudi Arabia from the viewpoint of two key stakeholders. This study attempts to address this knowledge gap.

This study aims to compare similarities and differences in library and information science (LIS) and non-LIS undergraduates’ conceptions and perceptions of smart libraries via drawing analysis.

In this study, a total of 156 undergraduate students described their perceptions of smart libraries as drawings and textual descriptions. A modified coding scheme with 8 categories and 51 subcategories was used to analyse the undergraduate students’ drawings.

Most of the undergraduate students’ conceptions of smart libraries still involve self-checkout and learning/reading, focusing on information appliances, technical services, activities and objects. The differences are that the LIS undergraduates’ drawings showed smart libraries with robots, interactive book borrowing with technology tools, intelligent services, location-aware services or mobile applications, whereas non-LIS undergraduates presented smart libraries as readers (learners), other activities and no smart technology services. LIS undergraduates focused on providing patron services with technologies. Non-LIS undergraduates were more likely to draw a complex space with immediate access to books or digital resources, quiet reading and the freedom to engage in library activities.

The results provide a baseline for future research on the topic and provide preliminary evidence of using the methods to discern LIS and non-LIS undergraduates’ conceptions of smart libraries.

This paper aims to examine how consumers make choices when they are faced with a fixed set of available options, consisting of both preferred and less-preferred choices, in the domain of food consumption. Specifically, the paper offers a novel perspective to predict repeated choice decisions in food consumption, which is termed as “pattern-seeking” – a consumption choice pattern that involves a coherent repetitive sequence of sub-groupings or coherently concentrated sub-groupings of options.

Eight experimental studies that contrast the existing theoretical predictions regarding repeated choices (e.g. primacy effect, recency effect, variety vs consistency) against pattern-seeking were conducted using hypothetical and actual food choices.

The results of experimental studies show that an explicit decision pattern (i.e. pattern-seeking) emerges as the most significant predictor of repeated choice in the food consumption domain.

This study offers a novel perspective on how consumers make repeated choices in the domain of food consumption.

The results show that consumers prefer food consumption with a pattern (vs non-pattern). Thus, it would be better to generate marketing activities that allow customers to satisfy their pattern-seeking more easily.

This study advances the literature on repeated food choices by demonstrating that people possess an inherent preference for patterns in food consumption.