Search results

This study aims to find the impact of the trade war between the USA and China on Asian economies. Apart from macroeconomic variables associated with trade, this study explicitly creates a trade war scenario and trade war participant dummies. Using the neural network multilayer perceptron, this study checks for the causal linkages between the predictors and target output for the panel of Asian economies and the USA.

A conceptual model of the after effects of trade war in a quadrant is developed. Variables related to trade and tariffs are included in the study for a panel of 19 Asian economies. The feedforward structure of neural network analysis is used to identify strong and weak predictors of trade war.

The hidden layers of the multilayer perceptron reveal the inconsistency in linkages for the predictors’ services exports, tariff measures, anti-dumping measures, trade war scenario dummy with gross domestic product. The findings suggest that to curtail the impact of the trade war on Asian economies, predictors with neural evidence must be paid due weightage in policy determination and trade agreements.

The study applies a novel and little explored AI/ML technique of Neural Network analysis with training of 70% observations. The paper will provide opportunity for other researchers to explore techniques of AI/ML in trade studies.

The increasing accumulation of synthetic plastic waste in oceans and landfills, along with the depletion of non-renewable fossil-based resources, has sparked environmental concerns and prompted the search for environmentally friendly alternatives. Biodegradable plastics derived from lignocellulosic materials are emerging as substitutes for synthetic plastics, offering significant potential to reduce landfill stress and minimise environmental impacts. This study highlights a sustainable and cost-effective solution by utilising agricultural residues and invasive plant materials as carbon substrates for the production of biopolymers, particularly polyhydroxybutyrate (PHB), through microbiological processes. Locally sourced residual materials were preferred to reduce transportation costs and ensure accessibility. The selection of suitable residue streams was based on various criteria, including strength properties, cellulose content, low ash and lignin content, affordability, non-toxicity, biocompatibility, shelf-life, mechanical and physical properties, short maturation period, antibacterial properties and compatibility with global food security. Life cycle assessments confirm that PHB dramatically lowers CO₂ emissions compared to traditional plastics, while the growing use of lignocellulosic biomass in biopolymeric applications offers renewable and readily available resources. Governments worldwide are increasingly inclined to develop comprehensive bioeconomy policies and specialised bioplastics initiatives, driven by customer acceptability and the rising demand for environmentally friendly solutions. The implications of climate change, price volatility in fossil materials, and the imperative to reduce dependence on fossil resources further contribute to the desirability of biopolymers. The study involves fermentation, turbidity measurements, extraction and purification of PHB, and the manufacturing and testing of composite biopolymers using various physical, mechanical and chemical tests.

Established in 2010, Mellower Coffee has 40 exquisite chain stores and three branches, namely Mellower Coffee Sales, Mellower Business Management and Shanghai Mellower Roasting Factory. Positioned as a premium coffee brand in China, Mellower Coffee has realized the integrated operation and management of the whole industrial chain from raw coffee trade, roasting factory, coffee retail products, specialty coffee chain, office coffee to coffee academy. It has a vision to attract and cultivate more and more coffee lovers by constant innovation coffee culture promotion.

Chapter 5 opens with a fictional scenario of a Professor of Digital Marketing on the US East Coast, who is making a cup of coffee in the morning and reflecting on the climate impact of the coffee journey at the same time as considering how she could incorporate this knowledge into her lectures in an impactful way. The Professor is considering designing an authentic piece of assessment which leads to behaviour change and has positive impact on society. The mentoring conversation she engages in is with a former colleague who has extensive experience of education-focused initiatives in universities and is an active mentor in great demand in the scholarly community. The conversation builds on Molthan-Hill and Blaj-Ward (2022), a point-of-departure paper about assessing climate solutions in a personally and societally meaningful way.

The synthesis of scholarly literature which follows the scenario and conversation has two points of focus. One is assessment. Relevant literature is referenced to further contextualize themes such as alignment, authenticity, well-being, sustainability, inclusivity and meaningful use of digital tools in assessment to develop identities and spark action. The other is the overlap between mentoring and coaching; a combination of the two is likely to support richer professional development for academics and, consequently, for their students. Climate-focused approaches in coaching have more recently been developed and are being used to facilitate resourceful responses to climate change. Two volumes on climate coaching are reviewed, to offer insights into the process of linking professional knowledge and life experience.

The past is important for various known and unknown reasons. This paper aims to reveal and justify unacknowledged reasons why, when and how managers should consider leveraging the pasts of previously successful but currently declining brands to restore their more desirable historical market positions.

This conceptual paper combines marketing and branding theory with historical branding examples, anecdotes and inductive inferences to develop and justify brand-pastness as a theoretically-grounded and managerially-actionable repositioning concept that could be applied to resurrect declining brands.

The emergent historically-grounded brand-pastness framework generates innovative insights that could be applied in the future. These insights explain when, why and how brand managers could apply brand-pastness to resurrect declining brands. The framework also facilitates the development of a brand-pastness-based research agenda. The agenda is driven by questions structured to address the nature, scope and potential applications of brand-pastness as a new concept and useful repositioning tool.

This paper’s recommendations are limited by their conceptual and inductive origins. However, a research agenda is developed to guide and structure future empirical investigations of the branding antecedents to and consequences of a prospective brand-pastness construct.

This paper introduces, conceptualizes and justifies the potential value of a historically-grounded concept called brand-pastness. The concept may prove beneficial when marketing managers use brand-pastness to reposition and resurrect declining brands by re-instilling targeted consumers’ historical perceptions of brands’ past superiority.

In the present study, using a novel fractional logit model, the link between R&D (Research & Development) investment and shareholder value-based CEO (Chief Executive Officer) compensation has been examined within the non-financial sector in the Euro area economies using a firm-level dataset for 2002–2019.

The fractional logit model is utilized to examine the effects of corporate payment on R&D investment. The fractional logit model can be considered the empirical approach that takes into account R&D non-performer firms to avoid reducing the sample size. The fractional logit model is superior to the censored or truncated models, like Tobit, since the fractional logit model is useful to address the econometric limitations that are found in the censored and truncated models in the non-linear models.

The findings obtained in this study showed a significant and negative effect of short-term aim-based CEO payment on R&D expenditures in the Euro area economies using firm-level data. These findings are robust to different robustness checks and modeling alternatives.

To the author's knowledge, there is no study that examines the effects of short-term shareholder value maximization-based CEO compensation on R&D in the European context in the literature.

The American agricultural economist Marion Clawson advised the Israeli government during 1953–1955. Clawson, a protégé of John D. Black and Mordecai Ezekiel, criticized the government for ignoring economic considerations, and stated that Israel’s national goals – defense, Negev Desert irrigation, immigrant absorption via new agricultural settlements, and economic independence – were mutually contradictory. His major recommendations were to improve the realism of Israel’s agricultural plan; end expensive Negev irrigation; enlarge irrigated farms eightfold; freeze new settlements until the number of semi-developed settlements falls from 300 to 100; and limit new Negev settlements to 10 over 5–7 years. Thus, Clawson ignored political feasibility and made value judgments. Minister of Finance Levi Eshkol and Minister of Agriculture Peretz Naphtali rejected Clawson’s recommendations because they ignored Israel’s national goals. By September 1954, Clawson shifted towards greater pragmatism: He acknowledged that foreign advisors should not question the national goals or make value judgments, and sought common ground with the Ministry of Agriculture. At his initiative, he wrote Israel Agriculture 1953/54 in collaboration with the Ministry of Agriculture. Israel Agriculture was a consensus document: Clawson eschewed recommendations and accepted that the government might prioritize non-economic goals. In proposing Israel Agriculture, Clawson made a pragmatic decision to relinquish some independence for (potentially) greater influence. Ultimately, Clawson was largely unsuccessful as an advisor. Clawson’s failure was part of a general pattern: Over 1950–1985, the Israeli government always rejected foreign advisors’ recommendations unless it was facing a severe crisis.

Data science promises new opportunities for organizational decision-making. Data scientists arguably play an important role in this regard and one can even observe a certain “buzz” around this nascent occupation. This paper enquires into how data scientists construct their occupational identity and the challenges they experience when enacting it.

Based on semi-structured interviews with data scientists working in different industries, the authors explore how these actors draw on their educational background, work experiences and perception of the contemporary digitalization discourse to craft their occupational identities.

The authors identify three main components of data scientists’ occupational identity: a scientific mindset, an interest in sophisticated forms of data work and a problem-solving attitude. The authors demonstrate how enacting this identity is sometimes challenged through what data scientists perceive as either too low or too high expectations that managers form towards them. To address those expectations, they engage in outward-facing identity work by carrying out educational work within the organization and (paradoxically) stressing both prestigious and non-prestigious parts of their work to “tame” the ambiguity and hype they perceive in managers’ expectations. In addition, they act upon themselves to better appreciate managers’ perspectives and expectations.

This study contributes to research on data scientists as well as the accounting literature that often refers to data scientists as new competitors for accountants. It cautions scholars and practitioners alike to be careful when discussing the possibilities and limitations of data science concerning advancements in accounting and control.

Micro-businesses contribute to economic development by improving individual welfare. Women are the primary drivers and owners of such businesses in urban Ethiopia. The purpose of this study is to investigate the poverty status and determinants among women-owned micro-businesses.

The basic study units were women who owned micro-businesses. A sample of 384 women-owned micro-business was chosen using a stratified and systematic random sampling technique. Thirty-six participants were purposely chosen for in-depth interviews and focus group discussions. Questionnaires, in-depth interviews and focus group discussions were used to collect data. The poverty head count, poverty gap and poverty severity indices were computed to estimate poverty status. The major determinants of women’s poverty were investigated using a logistic regression model.

The overall poverty incidence, gap and severity were estimated to be 24.27%, 3.85%, and 1.11% respectively, among the women who owned micro-businesses. Eight of the 14 poverty determinants, including age, dependents, savings, remittance and the number of days and hours women work in their businesses, were found to have a significant effect on women’s poverty. The results suggest that local governments, technical and vocational training institutions should work together to reduce the impact of poverty-aggravating factors on women and increase the contribution of women-owned micro-businesses to poverty reduction.

This study addressed the poverty status of women who run micro-businesses, which is a crucial issue in Ethiopia’s urban context. It adds new knowledge to the issue of gendered economic participation, poverty reduction and poverty determinants in the Ethiopian context.