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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.

In public management research, the focus in the public value debate has been on public administration organizations’ broader societal outcomes. Public value describes how public administrations form a vital part of the social context in which people develop and grow. However, there has not yet been an analysis of how public administration contributes to happiness in society.

In this study, we empirically analyze the relationship between people’s happiness and the public value of public administration. Our approach is based on a unique Swiss survey dataset comprising 870 individuals.

We find a positive relationship between public administration’s public value and happiness. We also find preliminary evidence with a moderation analysis that the relationship between a value-creating public administration sector and self-reported happiness is stronger for public administration employees.

While correlation studies cannot claim causal explanations and common method bias may additionally limit any research in social science, we took a number of measures to mitigate related problem. We tested our model in two samples and took both several procedural techniques and a survey design minimizing common method bias.

The paper discusses implications for public sector performance measurement for public management and practitioners.

This study calls for a more positive view on the multiple functions public administration performs for society. After an era of critical voices, our study helps reclaim public administration as a positive force for society at large in times of grand challenges, such as climate crisis, demographics and digitization.

This study has highlighted the importance between public administration’s public value and happiness in Swiss public service organizations. The study also showed that an employment in the public administration contributes to the happiness of individuals and beyond to society.

Firms are subject to power from both upstream and downstream partners; those partners may have different or even opposing impacts on supply chain relationships and financial performance. The purpose of this study is to investigate how upstream and downstream dependence structures affect a firm's financial performance through upstream and downstream relational depth (DEP) and relationship extendedness (EXT).

Data representing both upstream and downstream supply chain perspectives was collected using a multiple-respondent survey and was further augmented using financial performance data from an archival database.

Dependence advantages (ADVs) and disadvantages from upstream and downstream partners affect relational mechanisms and firm performance differently. Only downstream ADV will enhance a firm's DEP and EXT and subsequently affect firm's revenue and profit. Contradictory to widely held belief, the results reveal that firms that maintain long-term relationships with buyers and suppliers may experience lower revenue/profit.

This research represents a significant step in understanding the economic ramifications of dependence by (1) highlighting the difference between upstream and downstream supply chain dependence structure and (2) understanding the indirect effects of dependence structure on financial performance.

This paper aims to assess the readiness of retail workers to use blockchain technology (BCT) to improve supply chain performance. The assessment was made via a quantitative approach taken using a theoretical framework based on Keller’s motivation model and self-determination theory in the BCT context.

The authors collected data from 567 retail workers from an emerging country through a structured survey questionnaire. The authors tested the hypotheses of the proposed model using Warp PLS 7.0 and controlled firm age, industry type and technological intensity.

Our findings may help firms in making the process of digital transformation inclusive. The authors found that supplier-based attention and motivation through BCT lead to supply chain performance, and that supplier-based satisfaction and trust achieved through BCT positively impact supply chain performance. Further, supplier-based relevance on raw material selection with the higher trust and motivation levels achieved through BCT was found to have a positive impact on supply chain performance.

IT supply chain applications are referred to as “lean” rather than “rich” because they still rely mainly on written and numerical means to present data. When the environment is less ambiguous, then less rich media can be used to facilitate communication. IT supply chain applications allow suppliers to spend time building relationships with other suppliers instead of focusing on administrative tasks, thus enhancing such relationships.

This study can be considered the first to assess retailer readiness to use BCT to improve supply chain performance through the theoretical lens of Keller’s motivation model and self-determination theory.