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This study deals with changes in European Union's (EU's) trade potential in Machinery (HS 84–85) and Transportation (HS86-89) products.

The study uses a Structural Gravity model, Poisson Pseudo Maximum Likelihood (PPML) estimation together with panel data for the years 2002–2018 and a two-step procedure that employs predicted values of bilateral trade to compare potential to actual trade.

Results for Machinery products suggest a potential to expand trade with existing Regional Trade Agreements (RTAs) in the American continent, and countries of the IGAD region in Africa. In Transportation, a high trade potential with RTAs is found in the Americas, Africa and the Middle East. Policy suggestions concentrate on opportunities for enhancing trade relations through trade liberalization and agreement proliferation.

There are no studies to date, that examine “collective” measure of EU trade potential, that treats the EU as a single country. Changes in existing opportunities to expand trade, common for EU members, are of special interest for policy formulation, especially after the recent turmoil presented by the Global Financial Crisis (GFC) and the Greek Economic Crisis (GEC). Treating the EU as a single entity, is necessary for the formulation of an effective, common, EU trade policy. This study concentrates on the manufacturing sector to examine existing opportunities for the EU to expand trade, after the GFC and the GEC. This article deals with Machinery (HS 84 and 85) and Transportation (HS 86 through 89) products as they comprise a significant part of total EU exports, reaching 41% of total exports in 2016. Finally, this study offers a unique illustration of results through trade potential heat maps.

This study aims to investigate how firms of different sizes respond to competitive pressure from peers.

This study employs machine learning techniques to measure competitive pressure based on management discussion and analysis (MD&A) documents and then utilises the constructed pressure indicator to explore the relationship between competitive pressure and corporate risk-taking behaviours amongst firms of different sizes.

We find that firm sizes are positively associated with their risk-taking behaviours when firms respond to competitive pressure. Large firms are inclined to exhibit a high level of risk-taking behaviours, whereas small firms tend to make conservative decisions. Regional growth potential and institutional ownership moderate the relationships.

Utilising text mining techniques, this study constructs a novel quantitative indicator to measure competitive pressure perceived by focal firms and demonstrates the heterogeneous behaviour of firms of different sizes in response to competitive pressure from peers, advancing research on competitive market pressures.

In theory, the impact of debt liquidity risk (DLR) on the firm's future growth is ambiguous. This study aims to examine the empirical relationship between the DLR and firms' growth rate using annual data for USA companies from 1976 to 2020.

Given the longitudinal nature of the data, the author uses OLS (ordinary least squares) regression methodology with fixed effects to control for unobserved characteristics that might affect the dependent variable. Instrument variable regression is also used to address the potential endogeneity problem.

The results show that firms having higher DLR, as proxied by more short-term debt, experience lower growth rate. An increase in firms' short-term debt decreases the firms' future growth rate as evidenced by lower assets, revenue and employee growth rate. Moreover, the authors' results show that small firms or firms with more investment opportunities grow fast if the firms take higher DLR. Finally, cyclical firms with higher DLR exhibit lower growth rate during the credit tighten period. The authors' results hold for both the pre-zero lower bound (ZLB) era and ZLB period.

To the authors' best knowledge, this is one of the earliest studies to carefully examine the effects of DLR on firms' growth rate. While prior research finds that firms with higher growth potential, measured by market-to-book (MTB) ratio, use more short-term debt, the authors' research directly addresses whether DLR affects firms' future growth rate. The authors’ findings also help explain why firms with high growth potential use more short-term debt.

The purpose of this paper is to measure the high-quality entrepreneurial efficiency of family-owned small- and medium-sized enterprises (SMEs) while exploring the potential determinants of their performance. This study places particular emphasis on the firms' technological competencies and internationalization efforts. The authors aim to shed light on the internal and external characteristics that impact the efficiency of family SMEs.

This study adopts a two-stage approach. In the first stage, a data envelopment analysis model is utilized to measure the high-quality entrepreneurial efficiency of family SMEs. To achieve this, this study considered as outputs three key quality aspects of entrepreneurship, namely innovativeness, export orientation and turnover rate, while the inputs were the number of employees and the business environment. Then, in the second stage, the efficiency scores are regressed against a set of environmental factors that may affect the efficiency. The proposed efficiency measurement models are utilized with a particularly rich dataset of 1,910 family SMEs from 35 developed countries.

The results demonstrated that the efficiency of family SMEs primarily engaged in the production of goods was significantly higher than those providing services. Importantly, the presence of barriers related to innovation and digitalization had a pronounced negative impact on efficiency. Additionally, scale-up firms exhibited higher levels of efficiency. When examining family SMEs within their national context, it was observed that non-EU countries and countries with a higher gross domestic product displayed significantly higher efficiencies.

The findings of this research provide guidance for the development of entrepreneurship-oriented policies that consider both the internal characteristics of family SMEs and the diverse socioeconomic contexts in which they operate.

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。

Tanzania is rich in small hydropower (SHP) potentials. However, many of these potentials have yet to be fully used, and more than two-thirds of its rural population lacks access to electricity. The purpose of this paper is to explore the role of SHP stations in improving rural welfare in the southern highlands of Tanzania. It further explores the history, cost-effective analysis and threats to the sustainability of SHP as one of the renewable energy sources.

The study uses a qualitative research design to explore respondents’ views on the role of SHP stations in facilitating rural electrification and welfare improvement. Primary data were gathered using semi-structured interviews with the 27 key informants and beneficiaries of SHP stations from the Southern Highlands of Tanzania. In addition, the study used documentary research to complement the information from the field survey.

The findings found that SHP stations enhance rural electrification and welfare by providing electricity in remote areas with sparse populations. They operate as standalone off-grids, often by church communities and individuals. However, the sustainability of SHP stations is hampered by challenges such as climate change impacts, high capital investment costs, heavy siltation of small reservoirs, skilled manpower shortages, limited local manufacturing capabilities and infrastructural issues.

The study contributes to the ongoing debate on renewable energy supply and uses, focusing on how SHP stations could contribute to sustainable rural electrification and achieve the 2030 United Nations agenda for sustainable development, which, among other things, aims to safeguard access to sustainable and modern energy and alleviate energy poverty.

The aim of the present study was to investigate the association of the empirical dietary index for insulin resistance (EDIR) and empirical lifestyle index for insulin resistance (ELIR) with the risk of nonalcoholic fatty liver disease (NAFLD) in Iranian adults.

In this case-control study, 120 cases of NAFLD and 240 controls aged ≥20 years were included. NAFLD was detected by a gastroenterologist using an ultrasonography test. The food frequency questionnaire was used to collect nutritional data and determine the score of EDIR in participants. ELIR was determined based on body mass index, physical activity and dietary pattern. The odds ratios (ORs) of NAFLD were reported across tertiles of EDIR and ELIR using a logistic regression test.

The mean±SD age and BMI of subjects were 41.8 ± 7.5 years and 27.4 ± 2.2 kg/m², respectively. In the age and sex-adjusted model, the odds of NAFLD were increased across tertiles of ELIR (OR = 3.00; 95% CI: 1.63–5.55, P_trend = 0.001). Also, based on the fully adjusted model, the odds of NAFLD were increased according to tertiles of ELIR (OR = 2.66; 95% CI: 1.38–5.10, P_trend = 0.006). However, no significant association was found between the higher score of EDIR and odds of NAFLD based on the age and sex-adjusted model (OR = 1.18; 95% CI: 0.68–2.05, P_trend = 0.52) and the multivariable-adjusted model (OR = 0.91; 95% CI: 0.48–1.70, P_trend = 0.87).

To the best of the authors’ knowledge, this was the first study to examine the role of the insulinemic potential of diet and lifestyle in predicting NAFLD risk. Our findings suggested that a lifestyle with a higher score of ELIR was positively associated with NAFLD risk. However, a diet with a higher score of EDIR was not related to the odds of NAFLD.

With access to the large-scale search data from Rightmove plc, the paper firstly indicated the possibility of using user-generated data from online property portals to predict housing market activities and secondly embraced a GIS approach to explore what people search for housing and what they chose and investigated the issue of mismatch between search patterns and revealed patterns. Based on the analysis, the paper contributes a visual GIS-based approach which may help planners and designers to make more informed decisions related to new housing supply, particularly where to build, what to build and how many to build.

The paper used the 2013 housing search data from Rightmove and the 2013 price data from Land Registry with transactions made after the search period and embraced a GIS approach to explore the potential housing demand patterns and the mismatch between searches and sales. In the analysis, the paper employed the K-means approach to group prices into five levels and used GIS software to draw maps based on these price levels. The paper also employed a simple analysis of linear regression based on the coefficient of determination to investigate the relationship between online property views and values of house sales.

The result indicated the strong relationship between online property views and the values of house sales, implying the possibility of using search data from online property portals to predict housing market activities. It then explore the spatial housing demand patterns based on searches and showed a mismatch between the spatial patterns of housing search and actual moves across submarkets. The findings may not be very surprising but the main objective of the paper is to open up a potentially useful methodological approach which could be extended in future research.

It is important to identify search patterns from people who search with the intention to buy houses and from people who search with no intention to purchase properties. Rightmove data do not adequately represent housing search activity, and therefore more attention should be paid to this issue. The analysis of housing search helps us have a better understanding of households' preferences to better estimate housing demand and develop search-based prediction models. It also helps us identify spatial and structural submarkets and examine the mismatches between current housing stock and housing demand in submarkets.

The GIS approach in this paper may help planners and designers better allocate land resources for new housing supply based on households' spatial and structural preferences by identifying high and low demand areas with high searches relative to low housing stocks. Furthermore, the analysis of housing search patterns helps identify areas with latent demand, and when combined with the analysis of transaction patterns, it is possible to realise the areas with a lack of housing supply relative to excess demand or a lack of latent demand relative to the housing stock.

The paper proves the usefulness of a GIS approach to investigate households' preferences and aspirations through search data from online property portals. The contribution of the paper is the visual GIS-based approach, and based on this approach the paper fills the international knowledge gap in exploring effective approaches to analysing user-generated search data and market outcome data in combination.

Research on high growth firms is booming yet a strong conceptual understanding of how these firms obtain (and sustain) rapid growth remains (at best) partial. The main purpose of this paper is to explore the role founders play in enabling episodes of rapid growth and how they help navigate this process.

This paper reports the findings from a qualitative study involving in-depth interviews with entrepreneurs enlisted onto a publicly funded high growth business accelerator programme in Wales. These interviews explored the causes of the firms rapid growth, their key growth trigger points and the organisational consequences of rapid growth.

The research reveals that periods of high growth are intrinsically and inextricably inter-linked with the entrepreneurial traits and capabilities of their founders coupled with their ability to “sense” and “seize” pivotal growth opportunities. It also demonstrates founder-level dynamic capabilities enable firms to capitalise on pivotal “trigger points” thereby enabling their progression to a new “dynamic state” in a firm’s temporal evolution.

The novel approach towards theory building deployed herein is the use of theoretical elaboration as means of extending important existing theoretical constructs such as growth “trigger points” and founder dynamic capabilities. To capitalise on these trigger points, founders have to undergo a process of “temporal transitioning” to effectively manage and execute the growth process in firms. The work also has important policy implications, underlining the need for more relational forms of support for entrepreneurial founders.

Shadegan County as a wetland area was selected because of its susceptibility to flooding hazards and inundation. The purpose of this paper is to analyze flooding hazard based on the analytical hierarchy process methodology.

The eight influencing factors (slope, distance from wetland, distance from river, drainage density, elevation, curve number, population density and vegetation density) were considered for flood mapping within the Shadegan County using analytical hierarchical process, geographical information system and remote sensing. The validation of the map was conducted based on the comparison of the historical flood inundation of April 21, 2019.

The results showed that around 32.65% of the area was under high to very high hazard zones, whereas 44.60% accounted for moderate and 22.75% for very low to the low probability of flooding. The distance from Shadegan Wetland has been gained high value and most of the hazardous areas located around this wetland. Finally, the observed flood density in the different susceptibility zones for the very high, high, moderate, low and very low susceptible zones were 0.35, 0.22, 0.15, 0.19, and 0.14, respectively.

To the best of the authors’ knowledge, the flood susceptibility map developed here is one of the first studies in a built wetland area which is affected by anthropogenic factors. The flood zonation map along with management and restoration of wetland can be best approaches to reduce the impacts of floods.