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Little is known about how individual differences play out in the process of authentic self-development (ASD) through workplace coaching. This article explores whether the Big Five personality traits and affective, behavioral, cognitive and desire (ABCDs) components of the Big Five personality traits were relevant to ASD, specifically examining the role of affect as a potential mediator.

In total, 176 clients' personality was assessed pre-coaching. Aspects of ASD (perceived competence, goal commitment, self-concordance and goal stability) were assessed post-coaching. Clients' affect balance (AB) scores were obtained post-session.

Multilevel path models showed that higher levels of mean AB (but not the slope) mediated the associations between personality and perceived competence and goal commitment. Personality predicted goal self-concordance, but these effects were not mediated by AB, neither personality nor AB predicted goal stability.

The authors encourage randomized controlled trials to further test findings of this study. Ruling out method variance is not possible completely. However, the authors put forth considerations to support the authors' claim that method variance did not overly influence our results.

These results suggest the necessity of an optimal experience of affect for ASD in workplace coaching and the understanding of how ABCDs, AB and ASD are related beyond coaching psychology.

A deeper understanding of personality processes is important for fostering ASD to meet the challenges of management development in the authors' volatility, uncertainty, complexity and ambiguity (VUCA) world.

This is the first study to test personality as a process in workplace coaching linking personality to one of the most valued leadership skills: authenticity.

This paper aims to identify and empirically analyze useful and applicable metrics for measuring and managing the sustainability performance of small and medium-sized enterprises (SMEs).

To achieve the objective of the paper, potential metrics were adopted from previous research related to industrial sustainability and an empirical analysis was carried to assess the applicability of the metrics by collecting empirical data from Italian footwear SMEs using a structured questionnaire. The SMEs were selected using a convenience sampling method.

The results of the within-case analysis and the cross-case analysis indicate that the majority of the metrics were found to be useful and applicable to each of the SMEs and across the SMEs, respectively. These metrics emphasized measuring industrial sustainability performance related to financial benefits, costs and market competitiveness for the economic sustainability dimension; resources for the environmental sustainability dimension; and customers, employees and the community for the social sustainability dimension.

Apart from the within-case analysis and cross-case analysis, it was not possible to conduct statistical analysis since a small number of SMEs were accessible to collect empirical data.

The findings of the paper have considerable academic, managerial and policy implications and will provide a theoretical basis for future research on measuring and managing industrial sustainability performance. By providing a set of empirically supported metrics based on the triple bottom line approach (i.e. economic, environmental and social metrics), this paper contributes to the existing knowledge in the field of industrial sustainability performance measurement.

The lack of suitable indicators tailored to manufacturing industries’ needs, particularly to small and medium enterprises (SMEs), has been the major challenge to measure and manage industrial sustainability performance. This paper aims to empirically analyze and select the useful and applicable indicators to measure sustainability performance in the context of SMEs.

A systematic review was carried out to identify potential sustainability indicators from the literature. A questionnaire was designed based on the identified indicators and then pretested with the selected industrial experts, scholars, and researchers to further refine the indicators before data collection from the Italian footwear SMEs. Fuzzy Delphi method with consistency aggregation method was applied to analyze and select the final indicators.

The study’s findings show that the selected indicators emphasized measuring progress toward achieving industrial sustainability goals in terms of increasing financial benefits, reducing costs, improving market competitiveness, improving the effectiveness of resources utilization, and promoting the well-being of employees, customers and the community. In doing so, Italian footwear SMEs can contribute to achieving the Sustainable Development Goals (SDGs) by promoting health and well-being, promoting sustainable economic growth, providing productive employment and decent work, and ensuring responsible consumption and production.

The results of this study have significant social implications in terms of promoting the well-being of employees, customers, and the community.

By providing empirically supported indicators tailored to measure and manage sustainability performance in the context of SMEs, this paper contributes to the existing knowledge in the field of industrial sustainability performance measurement. Furthermore, it links the selected indicators to their respective SDGs to provide policy implications.

The choice of crops to produce at a location depends to a large degree on the climate. As the climate changes and food demand evolves, farmers may need to produce a different mix of crops. This study assesses how much cropland may be subject to such upheavals at the global scale, and then focuses on China as a case study to examine how spatial heterogeneity informs different contexts for adaptation within a country.

A global agricultural economic model is linked to a cropland allocation algorithm to generate maps of cropland distribution under historical and future conditions. The mix of crops at each location is examined to determine whether it is likely to experience a major shift.

Two-thirds of rainfed cropland and half of irrigated cropland are likely to experience substantial upheaval of some kind.

This analysis helps establish a global context for the local changes that producers might face under future climate and socioeconomic changes. The scale of the challenge means that the agricultural sector needs to prepare for these widespread and diverse upheavals.

When a major landslide and floods devastated Freetown, Sierra Leone had just overcome the Ebola crisis, which had left its mark on socio-political relations between different disaster response actors. With international disaster response frameworks increasingly shifting to local ownership, the national government was expected to assume a coordinating role. However, in “post-conflict” settings such as Sierra Leone, intra-state and state–society relations are continuously being renegotiated. This study aimed to uncover the complexities of state-led disaster response in hybrid governance setting at national and community levels in the response to the 2017 landslide and floods.

During the four months of fieldwork in Freetown in 2017, semi-structured interviews and focus group discussions with various state, aid and societal actors were conducted.

The findings show that a response to policy building on the idea of a uniform state response did not take into account intra-state power politics or the complexity of Sierra Leone's hybrid governance.

This paper argues for a more nuanced debate in humanitarian governance and practice on the localisation of aid in post-conflict and fragile settings.

The study's findings contribute to the literature on the disaster–conflict nexus, identifying paradoxes of localised disaster response in an environment with strong national–local tensions. The study highlights intra-local state dynamics that are usually overlooked but have a great impact on the legitimacy of different state authorities in disaster response.

This paper aims to assess the rate and land category contributing to the changes in seven land-uses in the Kintampo North Municipality of Ghana and the effect of the decisions of land users on future landscapes.

LANDSAT images were classified to generate land use/cover maps to detect changes that had occurred between 1986 and 2014. In total, 120 farmers were also interviewed to determine their perceptions on land use changes. Interval, category and transition levels of changes were determined. Savanna woodland, settlement and forest were mostly converted to farmland in both intervals (1986-2001 and 2001-2014).

Results showed that rock outcrop, plantation, cropland and savanna woodland increased at an annual rate of 13.86, 1.57, 0.82 and 0.33 per cent, respectively, whilst forest, settlement and water body decreased at 4.90, 1.84 and 1.17 per cent annual rate of change, respectively. Approximately, 74 per cent of farmers will not change land use in the future, while 84.2 per cent plan to increase farm sizes.

The study shows that more land cover will be targeted for conversion as farmers expand their farmlands. There is the need for strict implementation of appropriate land use/cover policies to sustain food production in the region in this era of changing climate and population increase.

This research assessed the land use changes in the Kintampo North Municipality and its impacts on agriculture and carbon stocks release via land use changes. It identified how the decisions of the local farmers on land management will affect future landscape.

Research on grand challenges in the management literature is vibrant and growing. Given that the term “grand challenges” was first invoked in our field 10 years ago, it is timely to reflect on how we came to this point – and where we might go from here. In this article, we first explore the origins of the concept of grand challenges in order to trace core assumptions and developments and understand how they shape the current conversation about grand challenges in management scholarship. We next convey findings from our review of 161 papers that cite the editorial for a grand challenges special issue (George, Howard-Grenville, Joshi, & Tihanyi, 2016), uncovering four ways in which papers are shaping the conversation on grand challenges. Finally, based on our perspective on how we got here and where we are now, we make several suggestions for what should come next in driving forward research on grand challenges. We urge scholars to go beyond the study of collaboration for tackling grand challenges and shift toward a more critical, yet generative, exploration of their construction, persistence, and unintended consequences. We also call for increased attention to theorizing grand challenges to guide practitioners’ understanding of the nature of the thing they are trying to address. In these ways, we hope to inspire management scholars to leverage expertise on processes – not content per se – that shape how grand challenges manifest and how they may be tackled.

Several attack models attempt to describe behaviours of attacks with the intent to understand and combat them better. However, all models are to some degree incomplete. They may lack insight about minor variations about attacks that are observed in the real world (but are not described in the model). This may lead to similar attacks being classified as the same type of attack, or in some cases the same instance of attack. The appropriate solution would be to modify the model or replace it entirely. However, doing so may be undesirable as the model may work well for most cases or time and resource constraints may factor in as well. This paper aims to explore the potential value of adding information about attacks and attackers to existing models.

This paper investigates used cases of minor variations in attacks and how it may and may not be appropriate to communicate subtle differences in existing attack models through the use of annotations. In particular, the authors investigate commonalities across a range of existing models and identify where and how annotations may be helpful.

The authors propose that nuances (of attack properties) can be appended as annotations to existing attack models. Using annotations appropriately should enable analysts and researchers to express subtle but important variations in attacks that may not fit the model currently being used.

This work only demonstrated a few simple, generic examples. In the future, the authors intend to investigate how this annotation approach can be extended further. Particularly, they intend to explore how annotations can be created computationally; the authors wish to obtain feedback from security analysts through interviews, identify where potential biases may arise and identify other real-world applications.

The value of this paper is that the authors demonstrate how annotations may help analysts communicate and ask better questions during identification of unknown aspects of attacks faster,e.g. as a means of storing mental notes in a structured manner, especially while facing zero-day attacks when information is incomplete.

This paper aims to investigate the pricing of discretionary earnings in South Africa. This is a unique setting, as South African listed firms also report mandatory non-GAAP earnings (“headline earnings”).

Results are based on multivariate regression analyses for South African firms that report from 2010 to 2019.

Findings show that the value-relevance of discretionary earnings exceeds that of both GAAP earnings and headline earnings. In addition, placement of discretionary earnings reconciliations communicates information about the decision-usefulness of earnings.

Discretionary earnings remain the most value-relevant earnings measure, despite the divergent decision-useful characteristics offered by headline earnings and GAAP earnings. Therefore, the most decision-useful earnings reflect unique industry or firm characteristics rather than the assurance arising from regulation.

The purpose of this paper is to identify the variables that influence corporate real estate (CRE) decision-making and gauge their relative importance to each other, thereby understanding the consequent challenges/implications for CRE managers (CREM’s).

Interviews were undertaken with experienced CREM’s using the causal network elicitation technique to create decision networks for the variables they considered for the specifically defined scenario: dealing with surplus property from a change of business strategy. These networks illustrate the complexity of the mental representations required for the realignment of the CRE portfolio. The key variables are more extensive than alignment theory suggests, namely, financial stakeholders. Additional variables identified include risk, lease accounting, costs, financial analysis, business metrics and motivational drivers. The latter indicates the importance of self-esteem and peer recognition for CREM’s and financial benefits for the C-suite. Accordingly strategy alignment needs to incorporate CRE both in terms of strategy creation and implementation.

These networks illustrate the complexity of the mental representations required for the realignment of the CRE portfolio. The key variables are more extensive than alignment theory suggests, namely, financial stakeholders. Additional variables identified include risk, lease accounting, costs, financial analysis, business metrics and motivational drivers. The latter indicates the importance of self-esteem and peer recognition for CREM’s and financial benefits for the C-suite. Accordingly, strategy alignment needs to incorporate CRE both in terms of strategy creation and implementation.

This research appears to be the first that looks in detail at the mental representations used by decision-makers while making CRE decisions.