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Research has shown that science, technology, engineering and mathematics (STEM) self-beliefs and enjoyment are critical factors for predicting female students’ persistence in STEM degrees and careers. Studies have shown the positive effects of informal STEM learning experiences on female students’ self-beliefs. However, with the rise of all-female STEM learning experiences, such as summer camps, considering the potential advantages and disadvantages of co-ed options is important. Further, prior STEM education research has focused on sex differences in students’ self-efficacy and STEM career interests. Our study aims to examine within sex differences in secondary, female students (n = 104) who attend either a co-ed STEM camp or a same-sex STEM camp.

To examine potential differences, we conducted independent sample t-tests.

Results of the study include statistically significant differences in mathematics and science self-efficacy as well as STEM career interest after participating in their respective camps.

Further, prior research in STEM education has focused on between sex differences in students’ self-efficacy and STEM career interest.

The authors propose the concept of “Autonomic Cycle for innovation processes,” which defines a set of tasks of data analysis, whose objective is to improve the innovation process in micro-, small and medium-sized enterprises (MSMEs).

The authors design autonomic cycles where each data analysis task interacts with each other and has different roles: some of them must observe the innovation process, others must analyze and interpret what happens in it, and finally, others make decisions in order to improve the innovation process.

In this article, the authors identify three innovation sub-processes which can be applied to autonomic cycles, which allow interoperating the actors of innovation processes (data, people, things and services). These autonomic cycles define an innovation problem, specify innovation requirements, and finally, evaluate the results of the innovation process, respectively. Finally, the authors instance/apply the autonomic cycle of data analysis tasks to determine the innovation problem in the textile industry.

It is necessary to implement all autonomous cycles of data analysis tasks (ACODATs) in a real scenario to verify their functionalities. Also, it is important to determine the most important knowledge models required in the ACODAT for the definition of the innovation problem. Once determined this, it is necessary to define the relevant everything mining techniques required for their implementations, such as service and process mining tasks.

ACODAT for the definition of the innovation problem is essential in a process innovation because it allows the organization to identify opportunities for improvement.

The main contributions of this work are: For an innovation process is specified its ACODATs in order to manage it. A multidimensional data model for the management of an innovation process is defined, which stores the required information of the organization and of the context. The ACODAT for the definition of the innovation problem is detailed and instanced in the textile industry. The Artificial Intelligence (AI) techniques required for the ACODAT for the innovation problem definition are specified, in order to obtain the knowledge models (prediction and diagnosis) for the management of the innovation process for MSMEs of the textile industry.

This study aims to develop an econometric analysis of how modern agriculture can be a fundamental instrument for reducing the levels of multidimensional poverty in Uganda. It demonstrates the importance of agriculture in reducing inequalities amongst the poor while focusing on the relationship between increasing productions from modern agricultural practices and the poverty level across the country.

The study explores Box–Jenkins approach to cereal production data with the use of econometric analysis as the main tool to determine the implications of modern agricultural practices in Uganda. Most poor people around the world are in marginalized rural environments, and agriculture provides for their livelihoods. This makes agricultural development crucial for reducing multidimensional poverty on a large scale and needs development within agriculture to be enhanced. Education, health and standard of living are the three dimensions considered from the weighted indicators, amounting to 30%, to be categorized poor in the three dimensions.

Modernization of agriculture is an ultimate solution to multidimensional poverty reduction in Uganda through employment generation and the effects of food prices. Shreds of evidence support the theories that agricultural incomes together with the actual wages increase with a general rise in the rural non-agricultural economy. Results depict a close correlation between national income and GDP per capita which is a very significant indication that more application of agricultural technology would lead to a sub sequential improvement of livelihoods engaged in agricultural practices.

Agriculture remains a vital sector that employs a greater portion of the population in Uganda’s economy. Major roles have been played by the sector in the economy including employment opportunities, rural household incomes, food supplies and a reduction in poverty from a multidimensional front. Exploring the behavior of poverty level using modern agriculture as an indicator and its relationship with the poverty level arising from improved agricultural practices could provide a meaningful display of variation in poverty across the regions at the country level.

This paper contributes to the field of public services’ performance measurement systems by proposing a benchmarking-based methodology that improves the effective use of big and open data in analyzing and evaluating efficiency, for supporting internal decision-making processes of public entities.

The proposed methodology uses data envelopment analysis in combination with a multivariate outlier detection algorithm—local outlier factor—to ensure the proper exploitation of the data available for efficiency evaluation in the presence of the multidimensional datasets with anomalous values that often characterize big and open data. An empirical implementation of the proposed methodology was conducted on waste management services provided in Italy.

The paper addresses the problem of misleading targets for entities that are erroneously deemed inefficient when applying data envelopment analysis to real-life datasets containing outliers. The proposed approach makes big and open data useful in evaluating relative efficiency, and it supports the development of performance-based strategies and policies by public entities from a data-driven public sector perspective.

Few empirical studies have explored how to make the use of big and open data more feasible for performance measurement systems in the public sector, addressing the challenges related to data quality and the need for analytical tools readily usable from a managerial perspective, given the poor diffusion of technical skills in public organizations. The paper fills this research gap by proposing a methodology that allows for exploiting the opportunities offered by big and open data for supporting internal decision-making processes within the public services context.

The human resource and talent management fields have been increasingly focusing on the process and criteria to identify employees’ potential for career advancement due to their impact on the competitive advantage of organizations. This paper expands the extant theoretical and empirical evidence regarding these complex decisions, namely through the combined analysis of multidimensional sources of employees' capital.

This is a cross-sectional study. Data were collected from 384 individuals assessed by their line managers. The research model and hypotheses were tested using structured equation modeling.

The results show a positive and significant influence of four employees’ capital sources, namely: human capital (what you know), social capital (whom you know), psychological capital (who you are) and reputational capital (how others perceive us) with regard to judgments of potential for career advancement. The model explains 52% of the total variance in those judgments.

The data were collected using a questionnaire at a single point in time and thus, not allowing cause-effect inferences.

The results provide guidance to organizational leaders to improve the decision-making process regarding judgments of potential for career advancement.

To our knowledge, this is the first study to examine managers’ judgments regarding the potential for career advancement using four sources of employees' capital: human, social, psychological and reputational capital. Furthermore, it considers that reputation plays a mediation role.

:在人力資源和人才管理的領域裡,越來越多的焦點被放在找出員工職業發展所需潛能的過程和標準上,這是因為機構和組織的競爭優勢會受其影響。本文擬擴展關於這類複雜的判斷和決定的現存理論和經驗證據; 研究人員使用的方法為對員工資本的多維來源進行綜合分析。

:本研究為橫斷面研究。數據來自384 名受其直線經理評估的個別員工; 研究人員使用了結構方程模型,去測試其研究模型和各個假設。

:研究結果顯示,就員工職業發展所需潛能的判斷而言,存在著會帶來正面和重大影響的四個員工資本來源,這包括人力資本 (你所瞭解的事物) 、社會資本 (你所認識的人物) 、心理資本 (你是誰) 和聲譽資本 (我們予人的印象) 。有關的模型可說明判斷百分之五十二的總方差。

:由於數據的收集是於單一時間點和透過問卷調查而完成的,故未能收因果推斷的效果。

:研究結果給予組織領袖實際的指引,使他們在關於職業發展所需潛能的判斷上，能夠改善其決策的過程。

:就我們所知,本研究為首個研究、以四個員工資本來源,即人力資本、社會資本、心理資本和聲譽資本,去探討經理如何就職業發展所需的潛能作出判斷; 而且，本研究認為聲譽是扮演著調節角色的。

Strategic flexibility (SF) has become increasingly important for firms because of the fast changes in the external environment. In line with the practical importance of SF, an emerging research field has developed around it that has attempted to understand the nature of SF and the key relationships. The aim of this study is to unveil the semantic structure of the recent literature on SF and to suggest new promising areas for future research.

The authors conduct a systematic literature review with a bibliographic analysis technique, which allows authors to identify the main recent streams in the literature, as well as offer reflections and suggestions for future research.

The authors uncover three main emerging areas in the research on SF, namely SF as a dynamic capability, the role of knowledge management for SF and the relationship between a firm SF and the external environment. The authors put forward three avenues for future research on SF: Avenue 1. SF, business model innovation (BMI) and other dynamic capabilities (DC), Avenue 2. Digital technologies and SF/organizational agility and Avenue 3. SF and sustainability. Articles included in the special issue entitled “A strategic perspective on flexibility, agility and adaptability in the digital era” contribute to Avenue 2, thus paving the way for filling some of the identified gaps regarding the relationship between SF and digitalization.

To the best of authors’ knowledge, this is the first literature review on SF that uses a bibliometric approach to draw conclusions on the findings in the literature. The review contributes to the theoretical understanding of SF by illustrating and explicating core topics that have persisted over time, as well as by presenting three main avenues for further developing authors’ knowledge around SF.

The importance of sustainable development has become increasingly significant in today’s fast-paced world. The 17 sustainable development goals (SDGs) aim to solve a range of environmental, economic and social challenges, which requires global collaboration among governments and private organisations. In light of this, social entrepreneurship has garnered significant attention as it combines the social purpose of non-profits with the market-driven approach of for-profits to address SDG goals. Yet the cognitive processes underpinning the career decisions of social entrepreneurs remain underexplored. This study aims to develop and validate a scale to measure social entrepreneurial career decisions based on the appraisal of perceived challenges.

The study followed the steps of tool development and was carried out in three phases: item analysis, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

The final 20-item scale focuses on the appraisal components in pre-entry social entrepreneurial career decision-making and has four factors, which are relevance, coping potential, knowledge and resources and normative significance.

The study contributes to the literature on entrepreneurial cognition, specifically focusing on social entrepreneurship. The scale could guide model testing and quantitative research in social entrepreneurial cognition. The four-dimensional structure identified in the study may also have implications for researchers interested in the antecedents and effects of social entrepreneurial decision-making.

Accurate measurement of cognitive appraisal is necessary to understand the perceived challenges and thought processes of potential social entrepreneurs. The scale could be used to examine the cognitive appraisal patterns among students. Social entrepreneurship educators and policymakers can use the scale to design and assess educational programs.

Distinct from existing studies, this scale offers a multidimensional approach that captures the stages of career decision-making, providing a robust tool to enhance our understanding of the decision-making dynamics in social entrepreneurship.

One of the issues currently being discussed around the globe, and especially in the tourism industry, is revisit intention. This study uses a bibliometric analysis strategy based on the Web of Science (WOS) database to examine the literature on revisit intention.

In this study, a sample of 482 articles was analyzed. The R programming language was used to process the data and graph the results.

The results found the occurrence of publications by year, publication source information and authors, journals, countries, institutions, thematic maps, current trends of topics in hospitality and tourism toward revisiting intention, and the most cited papers in revisit intention. This study highlights the importance of revisiting intention in the hospitality and tourism industry. The bibliometric analysis helps to set the research agenda on revisit intention.

To the best of the authors’ knowledge, this is the first study of its kind to present an empirical evaluation of revisit intention using inclusive mapping.

This study investigates to what extent the values perceived by tourists throughout cultural tours impact their overall satisfaction levels and behavioral intentions related to the destination. This study further examines the moderating role of tour guide competency in the relationship patterns concerned.

Empirical data were collected via a survey from 420 foreign tourists who visited Cappadocia and participated in guided cultural tours. Partial least squares-structural equation modeling was used for data analysis.

Study results reveal that the effects of quality, emotional, monetary and social value perceptions of tourists gained through cultural tour experiences on their overall satisfaction levels and the effects of overall satisfaction on recommendation and revisit intention are positive and significant. Furthermore, the moderating role of tour guide competency is significant and positive in the relationships between quality value and satisfaction and between satisfaction and revisit intention.

This study offers a critical analysis of discoveries concerning the pivotal role of tour guide competency within the cultural tour experience.

The purpose of this article is to illustrate an emerging typology that theoretically links work values with personal values and to provide evidence of construct validity for this typology.

A hypothesis was developed that four types of work values – intrinsic, extrinsic, prestige and affective – underlie the relative importance that individuals place on aspects of work. Evidence of construct validity was provided using triangulation analysis. Data from three different samples in Japan were analysed with three different techniques; exploratory factor analysis (N = 229), hierarchical cluster analysis (N = 244) and smallest space analysis (N = 203).

The results demonstrate acceptable internal consistency and a coherent structure that fits the theoretical model across methods and samples. These findings lend strong support to the use of the intrinsic, extrinsic, affective and prestige typology for studying work values. This will hopefully encourage field scholars to adopt the typology in future values-based explorations in the context of work.

The study adds to the emergent literature in business research that stresses the importance of triangulation analysis to enhance the reliability and validity of findings. In this sense, it is an innovative paradigm of a multiple triangulation approach, which combines both data and within-method triangulation. The methods employed covered – for the first time – all commonly applied techniques for exploring the structure underlying the data and provided inductive, deductive and spatial evidence to corroborate the observed structure of work values.