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How does the human brain absorb information and turn it into skills of its own in psychotherapy? In an attempt to answer this question, the authors will review the intricacies of processing channels in psychotherapy and propose the term transprocessing (as in transduction and processing combined) for the underlying mechanisms. Through transprocessing the brain processes multimodal memories and creates reparative solutions in the course of psychotherapy. Transprocessing is proposed as a stage-sequenced mechanism of deconstruction of engrained patterns of response. Through psychotherapy, emotional-cognitive reintegration and its consolidation is accomplished. This process is mediated by cellular and neural plasticity changes.

Recent studies in education attempt to ‘criminologise’ some of the current practices and policies of higher education institutions – that is, to deconstruct certain philosophies and practices which may be discriminatory, offensive, and biased to certain social groups. Recent theoretical frameworks problematize current higher education policies, many of which are taken for granted. This paper adopts a critical perspective, shedding light on some practices as they occur in higher educational institutions, by human and non-human agencies. The study applies a ‘detective’ approach examining some problematic uses of technology a higher education institution. In this proposed approach, researchers play the role of ‘detectives’, investigating possible breaches of good practice (possibly discriminatory) committed by higher education actors (referred hereafter as ‘defendants’). Most of these offences are committed through the use of educational and institutional technologies. The purpose of this theoretical approach is to empower alienated social groups against such practices by identifying ‘defendants’ and the implications of their acts. The study uses empirical data from interviews, visits, and observations to explain the ways in which defendants respond to the accusations levelled against them by other users of educational technologies. The investigation revealed that technology was used, among many other functions, to manoeuvre around the legal and ethical system serving the interests of some stakeholders. Then, the study categorises these manoeuvres, explaining the legal implications of each category, and recommending consideration of important academic and institutional issues.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

This study aims to present the climate change effect on potential evapotranspiration (ETP) in future periods.

Daily minimum and maximum temperature, solar radiation and precipitation weather parameters have been downscaled by global circulation model (GCM) and Lars-WG outputs. Weather data have been estimated according to the Had-CM3 GCM and by A1B, A2 and B1 scenarios in three periods: 2011-2030, 2045-2046 and 2080-2099. To select the more suitable method for ETP estimation, the Hargreaves-Samani (H-S) method and the Priestly–Taylor (P-T) method have been compared with the Penman-Monteith (P-M) method. Regarding the fact that the H-S method has been in better accordance with the P-M method, ETP in future periods has been estimated by this method for different scenarios.

In all five stations, in all three scenarios and in all three periods, ETP will increase. The highest ETP increase will occur in the A1B scenario and then in the A1 scenario. The lowest increase will occur in the B1 scenario. In the 2020 decade, the highest ETP increase in three scenarios will occur in Khorramabad and then Hamedan. Kermanshah, Sanandaj and Ilam stations come at third to fifth place, respectively, with a close increase in amount. In the 2050 decade, ETP increase percentages in all scenarios are close to each other in all the five stations. In the 2080 decade, ETP increase percentages in all scenarios will be close to each other in four stations, namely, Kermanshah, Sanandaj, Khorramabad and Hamedan, and Ilam station will have a higher increase compared with the other four stations.

Meanwhile, the highest ETP increase will occur in hot months of the year, which are significant with regard to irrigation and water resources.

This research aimed to examine entrepreneurial fear of failure and entrepreneurial well-being from the perspectives of incubated and nonincubated startups during crises.

Data were collected by distributing online questionnaires to 152 respondents comprising 43 incubated and 109 nonincubated startups in Indonesia. A multivariate discriminant analysis procedure was used to examine the interrelationships between both groups at the discovery, validation, customer creation and construction stages.

The result showed a significant difference between these startups at various stages, which was analyzed to provide insights into the relevant dimensions of fear of failure for startups. The essence of entrepreneurial well-being during crises is in accordance with the role of business incubators in an emerging market economy.

Startups need to innovate in order to grow while considering other factors such as work-life balance and financial resource availability. This is important to ensure they have sufficient motivating dosage of fear of failure.

The present study evaluates incubated and nonincubated startups in an emerging market economy by using both the entrepreneurial fear of failure and well-being to capture possible differences between groups. The context of pandemic crises helps us formulate appropriate approaches taken by incubators and startups in the future crises.

This study explores the awareness (AWN) levels of good governance amongst Thai credit union cooperatives' (CUCs) members and the factors hindering good governance practice in Thai CUCs.

This study used a survey questionnaire from 629 members of 36 selected CUCs in Thailand. This study analysed the determinants of governance AWN levels of Thai CUCs' members using the ordered probit model. The study also employs OLS estimation to investigate the factors hindering good governance practices.

The study shows that members of different CUC types and sizes have different levels of governance AWN. Members' characteristics, experiences, and perceptions significantly influence CUC members' AWN of governance issues. The findings also suggest that a lack of morality, transparency, participation, responsibility and accountability are key obstacles that hinder good governance practices of Thai CUCs.

This is the first study that attempts to assess the level of AWN amongst Thai CUCs' members in different CUC sizes and types. This is also the first research that identifies the factors that hinder good governance practice in Thai CUCs based on members' evaluations. The study's findings provide important reference and implications for Thai policy makers and CUCs' board of managers to enhance members' AWN and CUCs' governance performance, and thus increase income and living standard of CUCs' members in the long term.

The goal of this article is to provide an overview of healthcare entrepreneurship, both in terms of its current trends and future directions.

The article engages in a systematic review of extant research on healthcare entrepreneurship using the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) as the review protocol and bibliometrics or scientometrics analysis as the review method.

Healthcare entrepreneurship research has fared reasonably well in terms of publication productivity and impact, with diverse contributions coming from authors, institutions and countries, as well as a range of monetary and non-monetary support from funders and journals. The (eight) major themes of healthcare entrepreneurship research revolve around innovation and leadership, disruption and technology, entrepreneurship models, education and empowerment, systems and services, orientations and opportunities, choices and freedom and policy and impact.

The article establishes healthcare entrepreneurship as a promising field of academic research and professional practice that leverages the power of entrepreneurship to advance the state of healthcare.

The article offers a seminal state of the art of healthcare entrepreneurship research.

The purpose of this paper is to build a novel data envelopment analysis (DEA) model to evaluate the efficiencies of decision making units (DMUs).

Using the Choquet integrals as aggregating tool, the authors give a novel DEA model to evaluate the efficiencies of DMUs.

It extends DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form. At last, the authors use the numerical examples to illustrate the performance of the proposed model.

The proposed DEA model can be used to evaluate the efficiency of the DMUs with multiple interactive inputs and outputs.

This paper introduce a new DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form.

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。

This study aims to understand how businesses can contribute to the achievement of the UN sustainable development goals (SDGs) by implementing Local Agenda 21 (or equivalent) plans in partnership with other organizations situated in their city. To this end, the present study examines drivers and outcomes from the perspective of business partners, as well as their relationships to the SDGs.

Through a mixed-methods approach this research studies 71 businesses from four large cross-sector partnerships formed to achieve local sustainability goals. Data were collected through a survey to determine why firms partner and what outcomes they obtain from partnering. Qualitative content analyses are used to determine the relationships between business drivers and outcomes from partnering for local sustainability and the SDGs.

From a resource-based view (RBV) perspective, findings show the value of local sustainability partnerships in relation to the SDGs. Many SDG targets are aligned with the top reasons why businesses join large community sustainability partnerships. Also, through the outcomes achieved by participating in the partnership businesses can further the SDGs.

This research contributes to the literature and to practice through the understanding of businesses partnering for local sustainability, and its relationships to global sustainability. Firstly, the connections of business partners to local and global sustainability are better understood. Of note is the contribution made to the literature on sustainability-related drivers and outcomes expanding and refining RBV literature. Secondly, a positive connection has been established between businesses and the SDGs, proposing a virtuous model of relationship that summarizes the findings from this research. And thirdly, large cross-sector social partnerships are better understood.

Small- and medium-sized enterprises and large corporations with local offices can further both local and global sustainable development by engaging in local cross-sector sustainability partnerships.

These research findings are crucial for those leading sustainability initiatives, so they can engage businesses actively in light of the important role they play in society improving their contributions and the chances for sustainability partnerships to achieve their goals.

This research contributes to the scale conversation by exploring community sustainability partnerships as a means to understand how business engagement in sustainability at the local level can contribute to the achievement of the SDGs and, ultimately, to global sustainability.