Search results

The e-commerce boom presents new challenges for last-mile delivery (LMD), which may be mitigated by new delivery technologies. This paper evaluates the impact of mobile parcel lockers (MPL) on costs and CO₂ equivalent (CO₂e) emissions in existing LMD networks, which include home delivery and shipments to stationary parcel lockers.

To describe customers’ preferences, we design a multinomial logit model based on recipients’ travel distance to pick-up locations and availability at home. Based on route cost estimation, we define the operating costs for MPLs. We devise a mathematical model with binary decision variables to optimize the location of MPLs.

Our study demonstrates that integrating MPLs leads to additional cost savings of 8.7% and extra CO₂e emissions savings of up to 5.4%. Our analysis of several regional clusters suggests that MPLs yield benefits in highly populous cities but may result in additional emissions in more rural areas where recipients drive longer distances to pick-ups.

This paper designs a suitable operating model for MPLs and demonstrates environmental and economic savings. Moreover, it adds recipients’ availability at home to receive parcels improving the accuracy of stochastic demand. In addition, MPLs are evaluated in the context of several regional clusters ranging from large cities to rural areas. Thus, we provide managerial guidance to logistics service providers how and where to deploy MPLs.

The purpose of this paper is twofold: first, to review and classify scientific publications dealing with those innovative solutions aimed at increasing the efficiency of last-mile delivery in business to consumer (B2C) e-commerce; and, second, to outline directions for future research in this field.

The review is based on 75 papers published between 2001 and 2019 in international peer-reviewed journals or proceedings of conferences, retrieved from bibliographic databases and science search engines.

Due to its importance in affecting the overall logistics costs and, as a consequence, the economic sustainability of a B2C e-commerce initiative, last-mile delivery process deserves particular attention in order to be optimised. The review highlights that, among the main factors affecting its cost, there are the probability to have failed deliveries, the customer density in the delivery areas and the degree of automation of the process. Innovative and viable last-mile delivery solutions – which may impact the mentioned drivers – include parcel lockers, crowdsourcing logistics, mapping the consumer presence at home and dynamic pricing policies. Eventually, some gaps and areas for further research activities have been identified (e.g. mapping customer behaviour, crowdsourcing logistics).

This review offers interesting insights to both academics and practitioners. On the academic side, it analyses and classifies relevant literature about innovative and efficiency-oriented last-mile delivery solutions, proposing directions for future research efforts. On the managerial side, it presents a holistic framework of the main factors affecting last-mile delivery cost and of viable innovative solutions that may be implemented to increase efficiency.

The purpose of this paper is to examine factors influencing the audience demand for televised post-season games of the Korean professional baseball league.

The data were collected from a total of 129 games – the entire post-season games from 2008 to 2016. Two dependent variables representing audience demand for televised baseball matches, obtained from the third-party television audit company AGB Nielsen, were regressed on a series of match-related and unrelated antecedent factors associated with each match. Pooled OLS regression with wild bootstrap standard errors with 100,000 replications was applied in the analysis.

Regarding match-related factors, higher television ratings and the greater numbers of television viewers were associated with matches with greater significance, outcome uncertainty and score sum. In terms of the match-unrelated factors, the broadcast platform appeared to be the most powerful predictor of both television ratings and the numbers of viewers. Other than the broadcast platform, night matches, matches with full stadium occupancy and team values showed positive impacts on both the television ratings and the numbers of viewers.

The sales of media rights and sponsorships are the major sources of revenues for professional sports leagues, and the size of these two streams of revenues is in proportion to the size of the audience demand for television and other media. This study provides valuable insights to the sports marketers of professional sports clubs and leagues by establishing proper understanding of the determinants of the audience demand for televised sports.

The characteristics specific to each professional league and country play unique roles in determining the antecedent factors of audience demand for televised sports; this study is one of the few attempts to examine Koran professional baseball league.

This paper aims to investigate the impact of sources of information on trading behavior by analyzing the influence of investor personality in Chinese futures market.

The authors adopted the Big Five personality framework and examined the survey results of individual investors (n = 333) in Chinese futures market. Personality traits of futures investors were measured by the NEO-Five Factor Inventory (Costa and McCrae, 1989) which is a shortened version of revised NEO personality inventory of the Big Five model (Costa and McCrae, 1992). Confirmatory factor analysis was conducted to assess the fitness of model. Structural equation modeling was used to evaluate the moderating influence of investor personality traits on the association between source of information and trading behavior.

The results confirm the previous findings that the sources of information used by investors as a foundation of their financial choices have a significant impact on trading frequency. The authors also provide an empirical evidence that investor personality traits moderate the relationship between sources of information and trading behavior. Financial advice from professionals is likely to increase trading frequency in investors with neuroticism and openness personality traits, and to reduce trading frequency in conscientious and extravert investors. Similarly, financial information acquired via word-of-mouth communication results in more trading in extravert and agreeable investors. Finally, information acquisition from specialized press causes more adjustment of conscientious investors’ portfolios. Theoretical explanations, implications and recommendations for future research are discussed.

This study combines information search and behavioral finance literature to demonstrate that the impact of various sources of market information on asset allocation decisions is influenced by investor personality. No previous study has been conducted yet to explain variations in the impact of sources of information on trading behavior by the Big Five personality traits and this paper seeks to fill this gap in Chinese futures market.

This study aims to review the literature on sharing economy logistics and crowd logistics to answer the three following questions: How is the literature on sharing economy logistics structured? What are the main trends in sharing economy logistics and crowd logistics? What are the future research options?

Bibliometric analysis is used to evaluate 85 articles published over the past 12 years; it identifies the top academic journals, authors and research topics contributing to the field.

The sharing economy logistics and crowd logistics literature is structured around several disciplines and highlights that some are more scientifically advanced than others in their subject definitions, designs, modelling and innovative solutions. The main trends are organized around three clusters: Cluster 1 refers to the optimal allocation of costs, prices, distribution and supplier relationships; Cluster 2 corresponds to business related crowdsourcing and international industry practices; and Cluster 3 includes the impact of transport on last-mile delivery, crowd shipping and the environment.

The study is based on data from peer-reviewed scientific journals and conferences. A broader overview could include other data sources such as books, book chapters, working papers, etc.

Future research directions are discussed in the context of the evolution from crowd logistics to crowd intelligence, and the complexities of crowd logistics such as understanding how the social crowd can be integrated into the logistics process. Our results are part of the crowd science and engineering concept and provide some answers about crowd cyber-system questions regarding crowd intelligence in logistic sector.

The purpose of this paper is to systematically profile investors’ personality traits to examine if, and how, those traits are associated with phenomena observed in financial markets. In particular, the paper looks at overconfidence and overreaction in an experimental foreign exchange market.

The paper measures the personality of the subjects using the short form of the NEO-PIR instrument, the NEO-FFI developed by Costa and McRae (1992) which is based on Norman's (1963) “Big Five” personality constructs of negative emotion, extraversion, openness to experience, agreeableness and conscientiousness. The paper measures psychological gender using questions developed by Bem (1994). Preference for innovation and risk-taking propensity are measured using instruments developed by Jackson (1976). The paper then examines the behavior of the subject who traded interactively in “real time” in an interactive-simulated foreign exchange market where “price discovery” was instantaneous and pricing decisions were made instantaneously as items of news, determined by the researchers, were released.

The paper demonstrates that personality traits are associated with overconfidence and overreaction in financial markets. The paper presents meta-analysis which facilitates the development of a posteriori theories of how particular traits affect investment; there are important roles for risk-taking propensity, negative emotion, extraversion, masculinity, preference for innovation and conscientiousness.

A typical behavioral finance paper might find an empirical regularity in prices and, on the basis of such patterns, infer the underlying psychology motivating the behavior of investors. The approach differs from this caricature of the “typical” behavioral finance paper. The paper does not infer the underlying psychology of investors from patterns in prices. Rather, the paper learns about investors by systematically profiling their personality traits. The paper then demonstrates how those traits are associated with the prices generated by the investors the authors study. In focussing on the role of individual personality, the paper refocusses behavioral finance on the individuals who set prices.

The purpose of this study is to examine the role of personality traits (PTs) of individual investors on their investment intention (II). Further, to study the mediating role of overconfidence (OC) bias and financial literacy (FL) on the relationship between PTs and II.

The present study uses the quantitative approach for the data collection from the sample of 327 Indian investors investing in the stock market. The questionnaire was divided into segments to assess the investor’s PTs, OC, FL and II. The PT has been measured using the Big Five Personality Traits. Confirmatory factor analysis was used to test the reliability and validity of the constructs. The hypothesis was tested using structural equation modeling.

Findings of the study show that the PTs of an individual investor are associated with FL and II but insignificant with OC bias. Further, the FL and OC bias have a positive and significant influence on II. In addition, the mediation analysis showed that FL partly mediates the relationship between PTs and II.

The present study is helpful for financial companies, government, personal finance advisors and individual investors; they can keep in mind the behavior-related traits that can influence the investment decisions and design the portfolio accordingly. The policy-makers can implement programs on FL to enhance investment decisions in India.

This paper is unique that covers the mediating role of psychological bias, i.e. OC bias and FL, between the PTs and II of an Indian investor.

The aim of this study, the moderating effect of pleasure-seeking and loss aversion, was investigated in relation to the big five personality traits with regard to risky investment intentions.

In the study, the data was obtained between January and November 2019 via an online survey with convenience sampling. The total number of subjects is 886. The authors used IBM SPSS Statistics for analysis. Exploratory factor analysis, correlation analysis, regression analysis and discriminant analysis were performed.

Significant relationships were found between five personality traits and risky investment intentions. In these relationships, the moderator effect of pleasure-seeking for extraversion, conscientiousness and neuroticism personality traits was also determined. Besides, investment preferences for choosing “unknown and new investment” against “known and experienced investment”, which is a typical feature of the balloon periods, were modeled with big five personality traits and motivation variables (pleasure-seeking and loss aversion) and the equation was formed. As a result, high accuracy classification success was obtained.

The study is unique owing to its findings. In addition, general risk aversion and risky investment intention were investigated simultaneously to explain the different findings in the literature regarding the attitude of big five personality traits to risk and personality traits that show consistent approach were identified.

This paper aims to examine the effects of subjective and financial literacy, big five personality traits and emotions (fear, anger, hope and sadness) on risk aversion, risky investment intention and investment choices were investigated. Interactions of these three variables (risk aversion, risky investment intention and investment choices) were also examined.

For this purpose, in January-February 2019, collected data on 446 subjects from Turkey using the internet (341) and face-to-face (105) survey instruments. The authors exploited IBM SPSS Statistics for analysis. ANOVA, t-test and discriminant analysis were performed.

As a result of the analyzes, two personality traits (neuroticism and openness) and two emotions (fear and sadness) were determined as predictors of risk aversion. For risky investment intention, risk aversion, two personality traits (neuroticism and openness) and one of the same and other one different two emotions (fear and anger) were found.

Investment choices can be estimated by objective financial literature, risk aversion and risky investment intention. In addition, individuals’ risk averse or risk taking characteristics differ according to their level of sadness with agreeableness, conscientiousness and neuroticism personality traits. Similarly, have a risky investment intention or have not risky investment intention also differs according to sadness emotions with conscientiousness and openness. Finally, the choice of stocks or bank deposits varies according to subjective financial literacy and extraversion personality trait.

Logistics at work is rapidly changing. The changing trend is especially prominent when considering the active involvement of individuals that perform diverse forms of formal/informal “logistics work” (e.g. crowd logistics and self-collection). Thus, by conducting a synthesised review (n = 55), this study aims to provide a typology of individuals' logistics work.

The total social organisation of labour is used as a guiding framework. A deductive literature analysis is performed based on the identified journal articles.

The review findings reveal three major contexts where individuals perform logistics work: formal organisation, social community and private household, with a decreased level of formality. Under each context, individuals may be engaged in paid or unpaid activities, creating six forms of logistics work, termed as paid/voluntary professional logistics, incentivised/friendly social logistics and rewarded/free consumer logistics. Furthermore, an actor–sphere–resource–value conceptualisation of individual logistics is proposed, focussing on the chains of actors, work settings, resource input and value outcome.

The results provide a theoretical foundation for further research in individual- or consumer-centrism in logistics. Two research directions and seven research questions are presented for future investigation.