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The current advancements in technologies and the internet industry provide users with many innovative digital devices for entertainment, communication and trade. However, simultaneous development and the rising sophistication of cybercrimes bring new challenges. Micro businesses use technology like how people use it at home, but face higher cyber risks during riskier transactions, with human error playing a significant role. Moreover, information security researchers have often studied individuals’ adherence to compliance behaviour in response to cyber threats. The study aims to examine the protection motivation theory (PMT)-based model to understand individuals’ tendency to adopt secure behaviours.

The study focuses on Australian micro businesses since they are more susceptible to cyberattacks due to the least security measures in place. Out of 877 questionnaires distributed online to Australian micro business owners through survey panel provider “Dynata,” 502 (N = 502) complete responses were included. Structural equational modelling was used to analyse the relationships among the variables.

The results indicate that all constructs of the protection motivation, except threat susceptibility, successfully predict the user protective behaviours. Also, increased cybersecurity costs negatively impact users’ safe cyber practices.

The study has critical implications for understanding micro business owners’ cyber security behaviours. The study contributes to the current knowledge of cyber security in micro businesses through the lens of PMT.

This study aims to understand client food preferences and how pantry offerings can be optimized by those preferences.

This study develops and administers customized surveys to study three food pantries within the Second Harvest Food Bank of Northwestern North Carolina network. This study then categorizes food items by client preferences, identifies the key predictors of those preferences and obtains preference scores by fitting the data to a predictive model. The preference scores are subsequently used in an optimization model that suggests an ideal mix of food items to stock based upon client preferences and the item and weight limits imposed by the pantry.

This study found that food pantry clients prefer fresh and frozen foods over shelf-friendly options and that gender, age and religion were the primary predictors. The optimization model incorporates these preferences, yielding an optimal stocking strategy for the pantry.

This research is based on a specific food bank network, and therefore, the client preferences may not be generalizable to other food banks. However, the framework and corresponding optimization model is generalizable to other food aid supply chains.

This study provides insights for food pantry managers to make informed decisions about stocking the pantry shelves based on the client’s preferences.

An emerging topic within the humanitarian food aid community is better matching of food availability with food that is desired in a way that minimizes food waste. This is achieved by providing more choice to food pantry users. This work shows how pantries can incorporate client preferences in inventory stocking decisions.

This study contributes to the literature on food pantry operations by providing a novel decision support system for pantry managers to aid in stocking their shelves according to client preferences.

Although the effects of both news sentiment and expectations on price in financial markets have now been extensively demonstrated, the jointness that these predictors can have in their effects on price has not been well-defined. Investigating causal ordering in their effects on price can further our understanding of both direct and indirect effects in their relationship to market price.

We use autoregressive distributed lag (ARDL) methodology to examine the relationship between agent expectations and news sentiment in predicting price in a financial market. The ARDL estimation is supplemented by Grainger causality testing.

In the ARDL models we implement, measures of expectations and news sentiment and their lags were confirmed to be significantly related to market price in separate estimates. Our results further indicate that in models of relationships between these predictors, news sentiment is a significant predictor of agent expectations, but agent expectations are not significant predictors of news sentiment. Granger-causality estimates confirmed the causal inferences from ARDL results.

Taken together, the results extend our understanding of the dynamics of expectations and sentiment as exogenous information sources that relate to price in financial markets. They suggest that the extensively cited predictor of news sentiment can have both a direct effect on market price and an indirect effect on price through agent expectations.

Even traditional financial management firms now commonly track behavioral measures of expectations and market sentiment. More complete understanding of the relationship between these predictors of market price can further their representation in predictive models.

This article extends the frequently reported bivariate relationship of expectations and sentiment to market price to examine jointness in the relationship between these variables in predicting price. Inference from ARDL estimates is supported by Grainger-causality estimates.

Drawing on the social presence theory, this study aims to explore how supplier–customer social media interactions influence supplier observers’ trust in the customers and what mechanisms contribute to variation in trust experience.

A total of 36 semi-structured interviews were conducted with Chinese suppliers using WeChat for business-to-business interactions. Data were analyzed in three steps: open coding, axial coding and selective coding.

Findings reveal that varied trust is based not only on the categories of social presence of interaction – whether social presence is embedded in informative interactions – but also on the perceived selectivity in social presence. Observer suppliers who experience selectivity during social and affective interactions create a perception of hidden information and an unhealthy relationship atmosphere, and report a sense of emotional vulnerability, thus eroding cognitive and affective trust.

The findings contribute new understandings to social presence theory by exploring the social presence of interactions in a supplier–supplier–customer triad and offer valuable insights into business-to-business social media literature by adopting a suppliers’ viewpoint to unpack the mechanisms of how social presence of interaction positively and negatively influences suppliers’ trust and behavioral responses.

This study explores a hegemonic alliance and the role of relational forms of accounting and accountablity in the making of contemporary capitalism.

We use the WikiLeaks “Cablegate” documents to provide an account of the detailed machinations between interest groups (corporations and the state) that are constitutive of hegemonic activity.

Our analysis of the “Cablegate” documents shows that the US and Chevron were crafting a central role for Turkmenistan and its president on the global political stage as early as 2007, despite offical reporting beginning only in 2009. The documents exemplify how “accountability gaps” occlude the understanding of interdependence between capital and the state.

The study contributes to a growing idea that official accounts offer a fictionalized narrative of corporations as existing independently, and thus expands the boundaries associated with studying multinational corporate activities to include their interdependencies with the modern state.

The study traces how global capitalism extends into new territories through diplomatic channels, as a strategic initiative between powerful state and capital interests, arguing that the outcome is the empowerment of authoritarian states at the cost of democracy.

The study argues that previous accounting and accountability research has overlooked the larger picture of how capital and the state work together to secure a mutual hegemonic interest. We advocate for a more complete account of these activities that circumvents official, often restricted, views of global capitalism.

Land value in urban areas in India is influenced by regulations, bylaws and the amenities associated with them. Planning interventions play a significant role in enhancing the quality of the neighbourhood, thereby resulting in a change in its value. Land is a distinct commodity due to its fixed location, and planning interventions are also specific to certain locations. Consequently, the factors influencing land value will vary across different areas. While recent literature has explored some determinants of land value individually, conducting a comprehensive study specific to each location would be more beneficial for making informed policy decisions. Therefore, this article aims to examine and identify the critical factors that impact the value of residential land in the National Capital Territory of Delhi, India.

The study employed a combination of semi-structured and structured interview methods to construct a Relative Importance Index (RII) and ascertain the critical determinants affecting residential land value. A sample of 36 experts, comprising property valuers, urban planners and real estate professionals operating within the National Capital Territory of Delhi, India, were selected using snowball sampling techniques. Subsequently, rank correlation and ANOVA methods were employed to evaluate the obtained results.

Location and stage of urban development are the most critical determinants in determining residential land values in the National Capital Territory of Delhi, India. The study identifies a total of 13 critical determinants.

A scenario planning approach can be developed to achieve an equitable distribution of values and land use entropy. A land value assessment model can also be developed to assist professional valuers.

There has been a lack of emphasis on assessing the impact of planning interventions and territorial regulation on land values in the context of Delhi. This study will contribute to policy decision-making by developing a rank list of planning-based determinants of land value.

Digital transformation misalignment refers to disparities in digital transformation levels between suppliers and buyers across the production and operation process. It has negatively affected supply chain stability. However, the existing research concerning the economic consequences has not been adequately addressed. Therefore, this paper aims to investigate whether such digital transformation misalignment increases supplier financial risk and to identify the factors influencing this relationship.

This paper examines binary combinations of suppliers and buyers listed on China’s A-share market between 2011 and 2021. This group constitutes a sample to empirically test the influence of digital transformation misalignment on the supplier’s financial risk, as well as the moderating effect of the geographical and organizational distances.

The paper’s findings demonstrate that digital transformation misalignment has indeed a significant increase in the supplier’s financial risk. Moreover, the impact is more intense when the geographical or organizational distance between the supplier and the buyer is relatively large.

The existing literature rarely explores the potential risks arising from digital transformation misalignment between supply chain partners. Therefore, this paper fills a notable gap as it is the first to study the impact of digital transformation misalignment on the supplier’s financial risk and the specific applied mechanisms. The contribution significantly improves the field of corporate digital transformation, particularly, within the context of supply chain management.