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This study aims to establish the position of the European Union (EU-28) countries in the dynamics of international trade openness linkages and the Global Competitiveness Index (GCI) in correlation with the gross domestic product (GDP) per capita, research and development (R&D) expenditures, innovation capability and information and communication technology (ICT) adoption.

In the panel data set, comparative analyses were applied to scatter diagrams, correlation and regression analyses and structural equation models using Eurostat and World Economic Forum (WEF) data for the EU-28 countries in the period 2008–2019.

The empirical results did not confirm the hypotheses that a positive correlation exists between GCI and trade openness indicators and between GDP per capita and GCI. The ICT adoption and innovation capability increase GCI, which affects GDP per capita.

The empirical results provide a better understanding of the importance of trade policies, particularly in terms of trade openness and trade shares of the EU-28 countries, as it could contribute to increasing the GCI of the EU-28 countries. Furthermore, the results of this study underline the importance of ICT adoption and innovation capability and the need for appropriate government policies that improve global competitiveness.

This study, through empirical analysis, demonstrates the existence of correlations between trade openness (exports as % of GDP, imports as % of GDP and export market shares as % of world trade), R&D expenditures, innovation capability, ICT adoption, GDP per capita and the GCI in the EU-28 countries. In addition, this study contributes managerial and policy-based implications on driving forces of global competitiveness.

The purpose of this paper is threefold. First, it aims to clarify the moderating role of self-esteem (SE) and susceptibility to normative influence (SNI) in the relationship between brand love and brand loyalty. Second, the study proposes modeling the mediation role of brand love and outlining how SE and SNI affect the consumer-brand relationship. Finally, the study explores the impact of brand love on brand loyalty: the moderating role of self-esteem and social influences, as the literature regarding this is still lacking.

Data were collected via an online survey, which yielded 218 responses. Structural equation modeling was used to predict the research model.

The findings indicate that both SE and SNI mediate the relationship between brand love and brand loyalty. Additionally, consumers love the focal brands positively relates to SE and SNI. In return, SE and SNI lead to brand loyalty. The tight relationship of SE and SNI affects the connection between brand love and brand loyalty.

The data has been collected in Vietnam, which creates a limitation regarding the study’s cross-cultural nature and the economic context. Thus, the study should be conducted in different cultures and economies (both developing and developed countries) to enhance the generalizability in consumer-brand relationships.

Brand managers should conduct more advertising in brand communities to enhance the influence of SNI and emphasize unique features of the brands, to attract consumers through the overlap of SE.

The findings can contribute to enhancing unique brand identity and self-motivation will increase consumer loyalty, increasing the revenue of a specific brand. Moreover, as acceptable peers contribute to making purchase decisions, boosting the brand community will maintain current consumers and attract additional potential consumers from the current consumer relationships.

This study contributes to consumer psychology by indicating both SNI and SE as the mediators in the relationship between brand love and brand loyalty and how the consumer-brand relationship can be enabled.

El propósito de este trabajo es triple. En primer lugar, pretende aclarar el papel moderador de la autoestima (SE) y la susceptibilidad a la influencia normativa (SNI) en la relación entre el amor y la lealtad a la marca. En segundo lugar, el estudio propone modelar el papel mediador del amor a la marca y esbozar cómo la autoestima y la SNI afectan a la relación consumidor-marca. Por último, el estudio explora los factores que afectan a la relación entre el amor a la marca y la lealtad a la misma, ya que aún no existe literatura al respecto.

Los datos se recogieron mediante una encuesta en línea, que arrojó 218 respuestas. Se utilizó el modelo de ecuaciones estructurales (SEM) para predecir el modelo de investigación.

Los hallazgos indican que tanto la autoestima como la SNI median la relación entre el amor y la lealtad a la marca. Además, el amor de los consumidores por las marcas focales se relaciona positivamente con la autoestima y la SNI. En cambio, la autoestima y la SNI conducen a la lealtad a la marca. La estrecha relación de la autoestima y la SNI afecta la conexión entre el amor a la marca y la lealtad a la misma.

Los datos se han recogido en Vietnam, lo que crea una limitación en cuanto a la naturaleza transcultural del estudio y el contexto económico. Así pues, el estudio debería realizarse en diferentes culturas y economías (tanto de países en desarrollo como desarrollados) para aumentar la posibilidad de generalización en las relaciones entre consumidores y marcas.

Los gerentes de marca deberían hacer más publicidad en las comunidades de marcas para aumentar la influencia de la SNI y hacer hincapié en las características singulares de las marcas, a fin de atraer a los consumidores mediante la superposición de la autoestima.

Las conclusiones pueden contribuir a mejorar la identidad de una marca única, y la automotivación aumentará la lealtad de los consumidores, incrementando los ingresos de una marca específica. Además, como los pares aceptables contribuyen a la toma de decisiones de compra, el impulso de la comunidad de marcas mantendrá a los consumidores actuales y atraerá a otros consumidores potenciales de las relaciones de consumo actuales.

Este estudio contribuye a la psicología del consumidor al indicar que tanto la SNI como la autoestima son los mediadores en la relación entre el amor y la lealtad a la marca y la forma en que se puede habilitar la relación consumidor-marca.

摘要

本文有三方面的研究目的。第一，明确自尊（SE）和易受规范影响（SNI）在品牌喜爱与品牌忠诚关系中的调节作用。第二，建立品牌喜爱的中介作用模型，并概述SE和SNI如何影响消费者与品牌的关系。最后，探讨品牌喜爱对品牌忠诚度的影响：自尊和社会影响因素的调节作用，目前有关这方面的文献还比较缺乏。

通过在线调查收集数据，共收到218份答复。采用结构方程模型进行预测研究模型。

研究结果表明，自尊和易受规范影响都对品牌喜爱和品牌忠诚度之间的关系起到了调节作用。此外，消费者对焦点品牌的喜爱与自尊和易受规范影响具有正相关关系。反过来，自尊和易受规范影响又会导致品牌忠诚。自尊和易受规范影响的紧密关系影响了品牌喜爱和品牌忠诚之间的联系。

由于本次研究数据是在越南收集的，造成了研究的跨文化性质和经济背景的局限性。因此，未来的研究可以在不同的文化和经济体（包括发展中国家和发达国家）进行，以提高关于消费者与品牌关系结论的普遍性。

品牌管理者可以在品牌社区中增强广告宣传，提高易受规范影响的影响力，同时强调品牌的独特性，与自尊因素相结合来吸引消费者。

本文研究结果有助于增强独特的品牌识别和自我激励，提高消费者的忠诚度，增加特定品牌的收入。此外，由于合适的同伴有助于消费者做出购买决策，提升品牌社区可以维持现有消费者，并通过现有消费者关系吸引更多的潜在消费者。

本研究提出了自尊和易受规范影响是品牌喜爱和品牌忠诚关系的调节变量，并且进一步阐释了它们如何促成消费者与品牌的关系，从而为消费者心理学做出了贡献。

This paper examines empirically how growth opportunities determine the relationship between corporate diversification and firm's value in an emerging economy.

This study employs annual data of Indonesian manufacturing firm's spanning five years. To test the potential nonlinear relationship between diversification and value, nonlinear regression model is employed. Baron and Kenny’s (1986) procedure is also employed to test the mediation role of the growth opportunities in the relation between diversification strategy and firm's value. This study also performs further robustness analysis on mediating role of growth opportunities on the relationship between diversification strategy and corporate value using path analysis approach.

The analyses reveal the U-shaped diversification and value relationship; this result suggests that the effect of diversification on value will vary across firms, the negative effect of diversification strategy on firm's value may reverse at higher levels of diversification. Further analysis indicates that such relationship is fully mediated by firm's growth opportunities.

Given the results, firms that are considering implementing diversification strategy should seek the optimal level of diversification to gain diversification premium. Furthermore, the manager should observe the best opportunities available for the firm before undertaking the diversification strategies.

This paper contributes to the existing literature on diversification strategy by extending the insight of this research area of a large emerging economy, on which prior studies have not reached conclusive results.

Partial least squares (PLS) path modeling is a variance-based structural equation modeling (SEM) technique that is widely applied in business and social sciences. Its ability to model composites and factors makes it a formidable statistical tool for new technology research. Recent reviews, discussions, and developments have led to substantial changes in the understanding and use of PLS. The paper aims to discuss these issues.

This paper aggregates new insights and offers a fresh look at PLS path modeling. It presents new developments, such as consistent PLS, confirmatory composite analysis, and the heterotrait-monotrait ratio of correlations.

PLS path modeling is the method of choice if a SEM contains both factors and composites. Novel tests of exact fit make a confirmatory use of PLS path modeling possible.

This paper provides updated guidelines of how to use PLS and how to report and interpret its results.

Many important constructs of business and social sciences are conceptualized as composites of common factors, i.e. as second-order constructs composed of reflectively measured first-order constructs. Current approaches to model this type of second-order construct provide inconsistent estimates and lack a model test that helps assess the existence and/or usefulness of a second-order construct. The purpose of this paper is to present a novel three-stage approach to model, estimate, and test second-order constructs composed of reflectively measured first-order constructs.

The authors compare the efficacy of the proposed three-stage approach with that of the dominant extant approaches, i.e. the repeated indicator approach, the two-stage approach, and the hybrid approach by means of simulated data whose underlying population model is known. Moreover, the authors apply the three-stage approach to a real research setting in business research.

The study based on simulated data illustrates that the three-stage approach is Fisher-consistent, whereas the dominant extant approaches are not. The study based on real data shows that the three-stage approach is meaningfully applicable in typical research settings of business research. Its results can differ substantially from those of the extant approaches.

Analysts aiming at modeling composites of common factors should apply the proposed procedure in order to test the existence and/or usefulness of a second-order construct and to obtain consistent estimates.

The three-stage approach is the only consistent approach for modeling, estimating, and testing composite second-order constructs made up of reflectively measured first-order constructs.

This paper covers the development of a multidimensional contract administration performance model (CAPM) for construction projects. The proposed CAPM is intended to be used by the industry stakeholders to measure the construction contract administration (CCA) performance and identify the strengths and weaknesses of the CCA system for running or completed projects.

The research design follows a sequential mixed methodology of qualitative and quantitative data collection and analysis. In the first phase, contract administration indicators were collected from relevant literature. In the second phase, an online questionnaire was prepared, and data were collected and analyzed using the crisp value of fuzzy membership function, and structural equation modeling (SEM). The fuzzy set was chosen for this study due to the presence of uncertainty and fuzziness associated with the importance of several key indicators affecting the CCA performance. Finally, SEM was used to test and analyze interrelationships among constructs of CCA performance.

The data collected from 336 construction professionals worldwide through an online survey was utilized to develop the fuzzy structural equation model. The goodness-of-fit and reliability tests validated the model. The study concluded a significant correlation between CCA performance, CCA operational indicators, and the process groups.

The contribution of this paper to the existing knowledge is the development of a fuzzy structural equation model that serves as a measurement tool for the contract administration performance. This is the first quantitative structural equation model to capture contract administration performance. The model consists of 93 Construction Contract Administration(CCA) performance indicators categorized into 11 project management process groups namely: project governance and start-up; team management; communication and relationship management; quality and acceptance management; performance monitoring and reporting management; document and record management; financial management; changes and control management; claims and dispute resolution management; contract risk management and contract closeout management.

In their paper titled “A Miracle of Measurement or Accidental Constructivism? How PLS Subverts the Realist Search for Truth,” Cadogan and Lee (2022) cast serious doubt on PLS’s suitability for scientific studies. The purpose of this commentary is to discuss the claims of Cadogan and Lee, correct some inaccuracies, and derive recommendations for researchers using structural equation models.

This paper uses scenario analysis to show which estimators are appropriate for reflective measurement models and composite models, and formulates the statistical model that underlies PLS Mode A. It also contrasts two different perspectives: PLS as an estimator for structural equation models vs. PLS-SEM as an overarching framework with a sui generis logic.

There are different variants of PLS, which include PLS, consistent PLS, PLSe1, PLSe2, proposed ordinal PLS and robust PLS, each of which serves a particular purpose. All of these are appropriate for scientific inquiry if applied properly. It is not PLS that subverts the realist search for truth, but some proponents of a framework called “PLS-SEM.” These proponents redefine the term “reflective measurement,” argue against the assessment of model fit and suggest that researchers could obtain “confirmation” for their model.

Researchers should be more conscious, open and respectful regarding different research paradigms.

Researchers should select a statistical model that adequately represents their theory, not necessarily a common factor model, and formulate their model explicitly. Particularly for instrumentalists, pragmatists and constructivists, the composite model appears promising. Researchers should be concerned about their estimator’s properties, not about whether it is called “PLS.” Further, researchers should critically evaluate their model, not seek confirmation or blindly believe in its value.

This paper critically appraises Cadogan and Lee (2022) and reminds researchers who wish to use structural equation modeling, particularly PLS, for their statistical analysis, of some important scientific principles.

As technology in tourism and hospitality (TTH) develops technical artifacts according to visitors’ demands, it must deal with both behavioral and design constructs in the context of structural equation modeling (SEM). While behavioral constructs are typically modeled as common factors, the study at hand introduces the composite into TTH to model artifacts. To deal with both kinds of constructs, this paper aims to exploit partial least squares path modeling (PLS-PM) as a confirmatory approach to estimate models containing common factors and composites.

The study at hand presents PLS-PM in its current form, i.e. as a full-fledged approach for confirmatory purposes. By introducing the composite to model artifacts, TTH scholars can use PLS-PM to answer research questions of the type “Is artifact xyz useful?”, contributing to a further understanding of TTH. To demonstrate the composite model, an empirical example is used.

PLS-PM is a promising approach when the model contains both common factors and composites. By applying the test for overall model fit, empirical evidence can be obtained for latent variables and artifacts. In doing so, researchers can statistically test whether a developed artifact is useful.

To the best of the authors’ knowledge, this is the first study to discuss the practical application of composite and common factor models in TTH research. Besides introducing the composite to model artifacts, the study at hand also guides scholars in the assessment of PLS-PM results.

因为旅游酒店科技（TTH）根据游客需求而定制科技产品, TTH必须在结构方程模型（SEM）下结合游客行为和设计等变量。一般行为变量在模型中是常见因子, 本研究将这些变量编入TTH结构成为模块。本研究采用PLS-PM方法来预估含有隐性变量和模块的模型。.

本研究设计PLS-PM模式, 即确定性全变量方法。TTH学者们通过引进结构形成模型模块, 使用PLS-PM研究方法, 以回答研究问题“模块xyz有用吗？”, 因此对TTH进一步理解。为了展示复合模型, 本论文采用实际验证。.

PLS-PM在面对模块内存在常见因子和复合模块的结构时是有力方法。实际验证结果通过整体最佳模型参数, 得到隐性变量和模块。为此, 研究者们能够在统计方法上测量是否开发的模型模块是否有用。.

据作者所知, 本论文是首个研究在TTH领域上应用模块和常见因子模型。本研究引进显性变量在模型模块中, 以指导学者评估PLS-PM结果报告。.

This study aims to examine the role of an overall model fit assessment in the context of partial least squares path modeling (PLS-PM). In doing so, it will explain when it is important to assess the overall model fit and provides ways of assessing the fit of composite models. Moreover, it will resolve major concerns about model fit assessment that have been raised in the literature on PLS-PM.

This paper explains when and how to assess the fit of PLS path models. Furthermore, it discusses the concerns raised in the PLS-PM literature about the overall model fit assessment and provides concise guidelines on assessing the overall fit of composite models.

This study explains that the model fit assessment is as important for composite models as it is for common factor models. To assess the overall fit of composite models, researchers can use a statistical test and several fit indices known through structural equation modeling (SEM) with latent variables.

Researchers who use PLS-PM to assess composite models that aim to understand the mechanism of an underlying population and draw statistical inferences should take the concept of the overall model fit seriously.

To facilitate the overall fit assessment of composite models, this study presents a two-step procedure adopted from the literature on SEM with latent variables.

This paper clarifies that the necessity to assess model fit is not a question of which estimator will be used (PLS-PM, maximum likelihood, etc). but of the purpose of statistical modeling. Whereas, the model fit assessment is paramount in explanatory modeling, it is not imperative in predictive modeling.

The purpose of this paper is to unpack the underlying mechanisms of entrepreneurs' passion, orientation and behavior by investigating the role of rational and nonrational cognitive elements. Building on dual process theory and sociointuitionism, a conceptual model is proposed in order to explore the relationship between entrepreneurial passion, entrepreneurial orientation (EO) and strategic entrepreneurship behavior (SEB). Specifically, entrepreneurs' linear thinking styles (System 2) and nonlinear thinking styles (System 1) are hypothesized as being significant moderators of such a relationship.

Covariance-based structural equation modeling (CB-SEM) is used to empirically validate the proposed conceptual model and test the moderating hypotheses on a sample of 300 entrepreneurs actively involved in European small and medium enterprises (SMEs).

Entrepreneurial passion is shown to be a significant antecedent of EO, which, in turn, strongly influences SEB. Moreover, entrepreneurs' linear thinking style positively moderates the EO-SEB relationship, but not the link between passion and EO. Instead, a nonlinear thinking style positively moderates the relationship between passion and EO, but not the links between EO and SEB.

Entrepreneurs should trust their nonlinear thinking style – related to affective/emotive and intuitive information processing systems – to foster the effect of their entrepreneurial passion on EO. Furthermore, entrepreneurs should rely on a linear thinking style, namely the rational and deliberative cognitive processes, to enhance the impact of their EO on SEB.

Dual process theory and sociointuitionism are integrated to simultaneously investigate the effect of nonrational and rational cognitive mechanisms on entrepreneurs' orientation and behavior. Moreover, the proposed model is empirically tested on a sample of entrepreneurs working in SMEs located in Europe, which have received little attention from entrepreneurship scholars in comparison to their US counterparts. The authors’ findings suggest important implications for entrepreneurs, policymakers and entrepreneurial universities educators.