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This conceptual, multi-voiced paper aims to collectively explore and theorize family entrepreneuring, which is a research stream dedicated to investigating the emergence and becoming of entrepreneurial phenomena in business families and family firms.

Because of the novelty of this research stream, the authors asked 20 scholars in entrepreneurship and family business to reflect on topics, methods and issues that should be addressed to move this field forward.

Authors highlight key challenges and point to new research directions for understanding family entrepreneuring in relation to issues such as agency, processualism and context.

This study offers a compilation of multiple perspectives and leverage recent developments in the fields of entrepreneurship and family business to advance research on family entrepreneuring.

The purpose of this paper is to examine the determinants of users’ simulated experience in a virtual store and to show the subsequent impact of that experience on engagement. The outcome of that engagement is examined in relation to enjoyment, satisfaction and purchase intentions.

The method comprised an experiment comparing users’ perceptions of a standard 2D online clothing store with an enhanced, immersive one that aimed to provide shopping value approaching that of a traditional store by using a 3D experience where participants wore special glasses and a data glove.

Results demonstrate the major role of telepresence components in simulated experience and the critical role of that experience, along with hedonic and utilitarian values, in engagement. Purchase intention is influenced by satisfaction, which is in turn influenced by enjoyment and engagement. Engagement in turn is influenced by utilitarian and hedonic value and the experience of product simulation or telepresence, which is composed of control, colour and graphics vividness, and 3D authenticity. In the immersive, 3D environment, experience is more associated with engagement and enjoyment, leading to greater purchase intention. The immersive, 3D environment, thus, has the potential to rival traditional shopping in terms of experience, resulting in higher sales for retailers and satisfaction for consumers.

This work has evaluated a robust model of purchase intention and demonstrated it to hold not only in a 3D environment on a conventional computer platform, but also in an immersive one, where participants wear special glasses and a data glove.

This study aims at building a framework for the electronic word-of-mouth (eWOM) response under the social media environment. The elaboration likelihood model was adopted to explain how message source credibility and message appeal jointly influence the eWOM response process, while source credibility provides a central route and message appeal plays a peripheral route for information processing.

This study used a scenario design to test the decision behavior in the Facebook environment through message content manipulation. A convenience sampling method was adopted in this study. We collected 203 valid questionnaires and tested this research model with LISREL 8.8. This study used a two-stage structural equation modeling data analysis method with LISREL 8.8, by which the measurement model was assessed through confirmatory factor analysis for the reliability and validity of the research model, and the causal relationship among factors was assessed through exploratory factor analysis .

The results showed that 53% variance of eWOM responses could be explained by message source credibility and emotional message appeal from the elaboration likelihood model perspective. Message source credibility plays a central role in the social media environment. The model was further tested with a demographic profile analysis for both gender and age. It is found that a female user is influenced by both source credibility and emotional appeal, but a male user is only influenced by message source credibility. The mature age group is more responsive to eWOM messages.

The sample might not represent all social networking sites (SNS) users. The participants represent a small segment of the Facebook population around the globe. Secondly, this research design could be improved by using more recreational messages to test the effects of message appeal and message source credibility. Thirdly, the mobile phone is a type of physical product rather than an experiential product. Future studies could try to identify the same eWOM determinants with different SNS functions, for example, the inbox message function. Similarly, Facebook users are allowed to use both text and pictures to disseminate promotional messages.

This study provides an insight for SNS administrators regarding the determinants of driving more customer responses toward a message. Message source credibility and message appeal are identified as the antecedents for eWOM responses in SNS. Companies could make use of this finding to improve their marketing communication strategy in SNS. The finding can inform administrators of the importance of focusing on both customers’ psychological state and message attributes during the dissemination of promotional messages to improve the efficiency of the promotional effort. Companies aimed at receiving different types of eWOM responses in SNS may need to consider other factors for creating their promotional messages.

Previous studies have mainly identified factors influencing eWOM responses from the people-centered variables such as personal traits and social relationships. This study proposes that the eWOM response is a dual information processing process that can be explained by the ELM. When a user processes information in SNS, he follows both the central route and the peripheral route (i.e. source credibility and message appeal) which can influence the eWOM response. It is the first time that the source credibility is investigated as the central route in ELM model.

The development of written accuracy among learners of English as a Second Language (ESL) has always been a primary concern for ESL teachers and researchers in Applied Linguistics and Second Language Acquisition (SLA). While a vast body of research has examined written corrective feedback on students’ written products, few studies have focused on the development of written accuracy among Arabic speaking learners of English using automated feedback tools. This case study first examined the level of written accuracy of Bahraini learners of English in their second year at a higher education institute, highlighting the frequency of errors influenced by their first language (Arabic). The course following this first stage included a significant component of automated feedback on students’ writing; and this study explored the impact that the use of these feedback tools had on learners’ writing in English, tracking development over the course of an academic semester. A corpus of students’ initial writings and subsequent revisions was analysed to identify whether there was an improvement in the accuracy of students’ texts; and students’ perceptions were elicited.

ﻟط ﺎﻟ ﻣﺎ ﻛﺎ ن ﺗ طوﯾ ر اﻟدﻗﺔ ﻓ ﻲ ﻣﮭﺎ رة اﻟ ﻛﺗﺎﺑﺔ ﺑﯾ ن ﻣﺗ ﻌﻠ ﻣ ﻲ اﻟﻠ ﻐﺔ ا ﻹﻧ ﺟﻠﯾ زﯾﺔ ﻛﻠ ﻐﺔ ﺛﺎﻧﯾﺔ اﻟ ﺷـ ﻐ ل اﻟ ﺷـﺎ ﻏل ﻟ ﻣﻌﻠ ﻣ ﻲ اﻟﻠ ﻐﺔ ا ﻹﻧﺟ ﻠﯾ زﯾﺔ واﻟﺑﺎﺣ ﺛﯾ ن ﻓ ﻲ اﻟﻠ ﻐو ﯾﺎ ت اﻟ ﺗ ط ﺑﯾﻘﯾ ﺔ و ا ﻛﺗ ﺳ ـﺎ ب اﻟﻠ ﻐﺔ اﻟ ﺛﺎﻧﯾ ﺔ. ﻓ ﻲ ﺣ ﯾ ن أ ن ﻣ ﺟ ﻣو ﻋ ﺔ ﻛﺑﯾ ر ة ﻣ ن ا ﻷ ﺑ ﺣ ﺎ ث ﻗد د ر ﺳ ـ ت ﻣ ﻼ ﺣ ظ ﺎ ت ﺗ ﺻ ـ ﺣ ﯾ ﺣ ﯾ ﺔ ﺧ ط ﯾ ﺔ ﻋ ﻠ ﻰ ﻛﺗﺎﺑﺎ ت اﻟط ﻼ ب ، ﻓﻘ د رﻛز ت د را ﺳ ــﺎ ت ﻗﻠﯾﻠ ﺔ ﻋ ﻠ ﻰ ﺗ ط وﯾ ر اﻟ دﻗﺔ ﻓ ﻲ ﻣﮭﺎ رة اﻟ ﻛﺗﺎﺑ ﺔ ﺑﯾ ن ﻣﺗ ﻌﻠ ﻣ ﻲ اﻟﻠ ﻐﺔ ا ﻹ ﻧ ﺟ ﻠﯾ زﯾ ﺔ اﻟﻧﺎ ط ﻘﯾ ن ﺑﺎﻟ ﻌرﺑﯾ ﺔ ﺑﺎ ﺳ ــﺗ ﺧ دا م أدو ا ت اﻟ ﺗ ﻐذﯾ ﺔ ا ﻻ ﺳ ـــﺗ ر ﺟ ﺎ ﻋ ﯾ ﺔ ﻋ ﺑ ر ا ﻹ ﻧﺗ ر ﻧ ت . ﺗ ﺗ ﻧ ﺎ و ل د ر ا ﺳ ـ ـ ﺔ ا ﻟ ﺣ ﺎ ﻟ ﺔ ھ ذ ه أ و ﻻً ﻣ ﺳ ـ ـ ﺗ و ى ا ﻟ د ﻗ ﺔ ا ﻟ ﻣ ﻛ ﺗ و ﺑ ﺔ ﻟ ﻠ ﻣ ﺗ ﻌ ﻠ ﻣ ﯾ ن ا ﻟ ﺑ ﺣ ر ﯾ ﻧ ﯾ ﯾ ن ﻟ ﻠ ﻐ ﺔ ا ﻹ ﻧ ﺟ ﻠ ﯾ ز ﯾ ﺔ ﻓ ﻲ ﺳـ ﻧﺗ ﮭم اﻟﺛﺎﻧﯾ ﺔ ﻓ ﻲ ﻣؤﺳـ ﺳـ ﺔ ﻟﻠﺗ ﻌﻠﯾم اﻟﻌﺎﻟ ﻲ ، ﻣﻊ اﻟﺗ رﻛﯾ ز ﻋﻠ ﻰ ﺗﻛرا ر أ ﺧطﺎ ء اﻟﺗدا ﺧل ﺑﯾ ن اﻟﻠ ﻐﺔ ا ﻻوﻟ ﻰ واﻟﺛﺎﻧﯾﺔ. ﺛم ﺗ ﺳـﺗﻛ ﺷـ ف اﻟد را ﺳـ ﺔ ﺗﺄﺛﯾ ر أ دو ا ت اﻟ ﻣ ﻼﺣظﺎ ت ﻋﺑ ر ا ﻹﻧﺗ رﻧ ت ﻋﻠ ﻰ ﻛﺗﺎﺑﺔ اﻟ ﻣﺗ ﻌﻠ ﻣﯾ ن ﺑﺎﻟﻠ ﻐﺔ ا ﻹﻧ ﺟﻠﯾ زﯾﺔ ﻛﻠ ﻐﺔ ﺛﺎ ﻧﯾ ﺔ، وﺗ ﺗﺑ ﻊ اﻟﺗ طور ﺧﻼل اﻟﻔ ﺻ ـــ ل اﻟ د را ﺳـــ ﻲ. ﯾﺗ ﺿ ـــ ﻣ ن ا ﻟ ﺗ د ﺧ ل ا ﻟ ﻣ ط ﺑ ق ﻟ ﺗ ﺣ ﺳـ ﯾ ن ﺗ ﻧ ﻣ ﯾ ﺔ ﻣ ﮭ ﺎ ر ا ت ا ﻟ ﻣ ﺗ ﻌ ﻠ ﻣ ﯾ ن ﻣ ﻛ و ﻧًﺎ ﻣ ﮭ ﻣً ﺎ ﻟ ﻠ ﺗ ﻌ ﻠ ﯾ ق ﻋ ﺑ ر ا ﻹ ﻧ ﺗ ر ﻧ ت . ﻗ ﺎ ﻣ ت ا ﻟ د ر ا ﺳـ ﺔ ﺑ ﺗ ﺣ ﻠ ﯾ ل ﻣ ﺟ ﻣ و ﻋ ﺔ ﻣ ن ا ﻟ ﻛ ﺗ ﺎ ﺑ ﺎ ت ا ﻷ و ﻟ ﯾ ﺔ وا ﻟ ﻣرا ﺟﻌﺎ ت اﻟ ﻼﺣ ﻘﺔ ﻟﻠط ﻼ ب ، ﺑﺎﻹ ﺿ ﺎﻓﺔ إﻟ ﻰ ﻣر ا ﺟ ﻌﺎ ت اﻟ ﻧ ظ ر ا ء، ﻟﺗﺣ دﯾد ﻣﺎ إ ذا ﻛﺎ ن ھﻧﺎ ك ﺗ ﺣ ﺳ ن ﻓ ﻲ دﻗﺔ اﻟﻧ ﺻ و ص اﻟﻣﻛﺗ و ﺑ ﺔ ﻟﻠط ﻼ ب .

Background: Geostatistics focuses on spatial or spatiotemporal datasets. Geostatistics was initially developed to generate probability distribution predictions of ore grade in the mining industry; however, it has been successfully applied in diverse scientific disciplines. This technique includes univariate, multivariate, and simulations. Kriging geostatistical methods, simple, ordinary, and universal Kriging, are not multivariate models in the usual statistical function. Notwithstanding, simple, ordinary, and universal kriging techniques utilize random function models that include unlimited random variables while modeling one attribute. The coKriging technique is a multivariate estimation method that simultaneously models two or more attributes defined with the same domains as coregionalization.

Objective: This study investigates the impact of populations on traffic volumes as a variable. The additional variable determines the strength or accuracy obtained when data integration is adopted. In addition, this is to help improve the estimation of annual average daily traffic (AADT).

Methods procedures, process: The investigation adopts the coKriging technique with AADT data from 2009 to 2016 from Montana, Minnesota, and Washington as primary attributes and population as a controlling factor (second variable). CK is implemented for this study after reviewing the literature and work completed by comparing it with other geostatistical methods.

Results, observations, and conclusions: The Investigation employed two variables. The data integration methods employed in CK yield more reliable models because their strength is drawn from multiple variables. The cross-validation results of the model types explored with the CK technique successfully evaluate the interpolation technique's performance and help select optimal models for each state. The results from Montana and Minnesota models accurately represent the states' traffic and population density. The Washington model had a few exceptions. However, the secondary attribute helped yield an accurate interpretation. Consequently, the impact of tourism, shopping, recreation centers, and possible transiting patterns throughout the state is worth exploring.

Technology uncertainty poses significant challenges to manufacturers, as rapid changes in product and/or process standards and specifications can disrupt the smooth flow of materials in extended supply chains. Practitioners and researchers alike who take a relational perspective widely regard supplier involvement as a potentially effective strategy to cope with technology uncertainty, as focal manufacturers can tap into their upstream supply networks for complementary resources and capabilities. However, the literature lacks a nuanced understanding of the supplier involvement processes. Specifically, the role of resource dependence for supplier involvement has yet to be systematically understood. To fill this gap, this study aims to combine the relational perspective with the resource-dependence perspective to explore how buyer dependence, supplier dependence and buyer–supplier interdependence influence buyers’ decision-making on tapping into upstream supply networks for coping with technology uncertainty.

To test the hypotheses, a survey is conducted among Dutch firms with more than 50 employees in the discrete manufacturing industries (ISIC 28-35), resulting in a sample of 125 manufacturers.

First, there is a significantly positive relationship between technology uncertainty and supplier involvement, giving support to the expectation that buyers are indeed involving their key suppliers in the product/process design and improvement, as a response to technology uncertainty. Second, buyer dependence and interdependence are found to be positively moderating the relationship between technology uncertainty and supplier involvement. In contrast, supplier dependence has a negative moderating effect on the baseline relationship.

The authors contribute to a relational view on buyer–supplier relationships by showing that the validity of this view, in the context of technology uncertainty, is contingent on the resource dependence between buyers and suppliers, and the authors contribute to the supply chain management literature more generally by combining a relational perspective with a resource-dependence perspective.

The findings provide several nuanced insights into the effect of resource dependence (buyer dependence, supplier dependence and interdependence) on supplier involvement for coping with technology uncertainty.

This study contributes to the supply chain management research by going beyond the benefits of supplier involvement and highlights the circumstances under which supplier involvement is likely to occur.

Logistical facility location decisions can make a crucial difference in the success or failure of a company. Geographical Information Systems (GIS) have recently become a very popular decision support system to help deal with facility location problems. However, until recently, GIS methodologies have not been fully embraced as a way to deal with new facility location problems in business logistics. This research makes a framework for categorizing empirical facility location problems based on the intensity of the involvement of GIS methodologies in decision making. This framework was built by analyzing facility location models and GIS methodologies. The research results revealed the depth of the embracement of GIS methodologies in logistics for determining new facility location decisions. In the new facility location decisions, spatial data inputs are almost always coupled with the visualization of the problems and solutions. However, the usage of GIS capability solely (i.e. suitability analysis) for problem solving has not been embraced at the same level. In most cases, the suitability analysis is used together with special optimization models for choosing among the multiple alternatives.

This article examines the experiences of women leaders and their challenges in Brunei Darussalam. Globally, women are underrepresented in leadership positions. Though the Brunei government does not discriminate against any gender in delivering free education, medical facilities and healthcare, women in leadership positions are as well underrepresented. I try to understand the factors that challenge as well as motivate women to become leaders in Brunei. For this research, I conducted qualitative interviews with some respondents selected purposively. The study results show that women leaders in Brunei face challenges in obtaining financial support and accessing resources. Despite the challenges, there are some women who have been assuming and excelling in their leadership roles. The study identified that personal strengths have also been critical in contributing to their successful leadership.

The purpose of this paper is to investigate the effect of remelting each layer on the homogeneity of nickel-titanium (NiTi) parts fabricated from elemental nickel and titanium powders using laser powder bed fusion (LPBF). In addition, the influence of manufacturing parameters and different melting strategies, including multiple cycles of remelting, on printability and macro defects, such as pore and crack formation, have been investigated.

An LPBF process was used to manufacture NiTi alloy from elementally blended powders and was evaluated with the use of a remelting scanning strategy to improve the homogeneity of fabricated specimens. Furthermore, both single melt and up to two remeltings were used.

The results indicate that remelting can be beneficial for density improvement as well as chemical and phase composition homogenization. Backscattered electron mode in scanning electron microscope showed a reduction in the presence of unmixed Ni and Ti elemental powders in response to increasing the number of remelts. The microhardness values of NiTi parts for the different numbers of melts studied were similar and ranged from 487 to 495 HV. Nevertheless, it was observed that measurement error decreases as the number of remelts increases, suggesting an increase in chemical and phase composition homogeneity. However, X-ray diffraction analysis revealed the presence of multiple phases regardless of the number of melt runs.

For the first time, to the best of the authors’ knowledge, elementally blended NiTi powders were fabricated via LPBF using remelting scanning strategies.

Background: The annual average daily traffic (AADT) data from road segments are critical for roadway projects, especially with the decision-making processes about operations, travel demand, safety-performance evaluation, and maintenance. Regular updates help to determine traffic patterns for decision-making. Unfortunately, the luxury of having permanent recorders on all road segments, especially low-volume roads, is virtually impossible. Consequently, insufficient AADT information is acquired for planning and new developments. A growing number of statistical, mathematical, and machine-learning algorithms have helped estimate AADT data values accurately, to some extent, at both sampled and unsampled locations on low-volume roadways. In some cases, roads with no representative AADT data are resolved with information from roadways with similar traffic patterns.

Methods: This study adopted an integrative approach with a combined systematic literature review (SLR) and meta-analysis (MA) to identify and to evaluate the performance, the sources of error, and possible advantages and disadvantages of the techniques utilized most for estimating AADT data. As a result, an SLR of various peer-reviewed articles and reports was completed to answer four research questions.

Results: The study showed that the most frequent techniques utilized to estimate AADT data on low-volume roadways were regression, artificial neural-network techniques, travel-demand models, the traditional factor approach, and spatial interpolation techniques. These AADT data-estimating methods' performance was subjected to meta-analysis. Three studies were completed: R squared, root means square error, and mean absolute percentage error. The meta-analysis results indicated a mixed summary effect: 1. all studies were equal; 2. all studies were not comparable. However, the integrated qualitative and quantitative approach indicated that spatial-interpolation (Kriging) methods outperformed the others.

Conclusions: Spatial-interpolation methods may be selected over others to generate accurate AADT data by practitioners at all levels for decision making. Besides, the resulting cross-validation statistics give statistics like the other methods' performance measures.