Matt T. Morley, Jeffrey B. Maletta, Michael J. King, Robert V. Hadley, Matthew J. Fader and Brian F. Saulnier
The purpose of this paper is to explain and emphasize the importance of compliance with the Foreign Corrupt Practices Act and similar anti‐corruption laws in force in other…
Abstract
Purpose
The purpose of this paper is to explain and emphasize the importance of compliance with the Foreign Corrupt Practices Act and similar anti‐corruption laws in force in other countries.
Design/methodology/approach
The paper cites renewed pressure to address corruption risks from regulatory and other sources, and recommends compliance steps a firm can take to reduce the risk of legal liability.
Findings
FINRA has identified FCPA compliance as an examination priority for 2009, the UK Financial Services Authority (FSA) has recently taken a high‐profile disciplinary action against a firm for inadequate training and due diligence as to bribery and anti‐corruption risks, and FCPA enforcement is expected to remain a priority for the Obama Administration.
Originality/value
The paper presents practical guidance from experienced securities lawyers.
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Keywords
The following bibliography focuses mainly on programs which can run on IBM microcomputers and compatibles under the operating system PC DOS/MS DOS, and which can be used in online…
Abstract
The following bibliography focuses mainly on programs which can run on IBM microcomputers and compatibles under the operating system PC DOS/MS DOS, and which can be used in online information and documentation work. They fall into the following categories:
Matthew A. Waller, Andrea Heintz Tangari and Brent D. Williams
The purpose of this study is to investigate the impact of a key logistics and distribution variable, case pack quantity, on a consumer packaged goods (CPG) manufacturing firm's…
Abstract
Purpose
The purpose of this study is to investigate the impact of a key logistics and distribution variable, case pack quantity, on a consumer packaged goods (CPG) manufacturing firm's performance. The paper builds theory with respect to case pack quantity's dichotomous impact on the retail shelf replenishment process and subsequent impact on market share depending on product rate‐of‐sale (ROS).
Design/methodology/approach
The study empirically tests the case pack quantity phenomenon using monthly in‐store data collected over a two year time period, market share data and data provided by a leading US CPG manufacturer in the ready‐to‐eat cereal category. Regression analysis is used to determine if case pack quantity significantly impacts firm market share.
Findings
According to compelling theoretical and empirical evidence, the number of units per retail shipping container (case pack quantity) has a significant impact on retail market share. The evidence indicates that the effect of case pack quantity on market share depends upon the ROS of a given stock‐keeping unit (SKU). For faster selling SKUs, larger case packs should increase market share. For slower selling SKUs, larger case pack quantities reduce market share because of additional stockouts at the retail level, resulting from execution problems caused by the larger case pack quantities.
Practical implications
Given the study's findings, CPG manufacturing firms must align case pack quantities with SKU ROS to positively affect the shelf replenishment process.
Originality/value
The paper demonstrates that case pack quality has a significant impact on retail market share.
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Li Xiao, Hye-jin Kim and Min Ding
Purpose – The advancement of multimedia technology has spurred the use of multimedia in business practice. The adoption of audio and visual data will accelerate as marketing…
Abstract
Purpose – The advancement of multimedia technology has spurred the use of multimedia in business practice. The adoption of audio and visual data will accelerate as marketing scholars become more aware of the value of audio and visual data and the technologies required to reveal insights into marketing problems. This chapter aims to introduce marketing scholars into this field of research.Design/methodology/approach – This chapter reviews the current technology in audio and visual data analysis and discusses rewarding research opportunities in marketing using these data.Findings – Compared with traditional data like survey and scanner data, audio and visual data provides richer information and is easier to collect. Given these superiority, data availability, feasibility of storage, and increasing computational power, we believe that these data will contribute to better marketing practices with the help of marketing scholars in the near future.Practical implications: The adoption of audio and visual data in marketing practices will help practitioners to get better insights into marketing problems and thus make better decisions.Value/originality – This chapter makes first attempt in the marketing literature to review the current technology in audio and visual data analysis and proposes promising applications of such technology. We hope it will inspire scholars to utilize audio and visual data in marketing research.
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THE BBC's television services have a longer history than is generally realised. Experiments were going on in 1925 and 1926, broadcasts were being put out as early as 1933 or 1934…
Abstract
THE BBC's television services have a longer history than is generally realised. Experiments were going on in 1925 and 1926, broadcasts were being put out as early as 1933 or 1934, and on 2nd November, 1936 the BBC gave Great Britain the world's first regular television service, operating on the 405‐line standard in the Very High Frequency channels.
Julia B. Edwards, Alan C. McKinnon and Sharon L. Cullinane
The purpose of this paper is to focus on the carbon intensity of “last mile” deliveries (i.e. deliveries of goods from local depots to the home) and personal shopping trips.
Abstract
Purpose
The purpose of this paper is to focus on the carbon intensity of “last mile” deliveries (i.e. deliveries of goods from local depots to the home) and personal shopping trips.
Design/methodology/approach
Several last mile scenarios are constructed for the purchase of small, non‐food items, such as books, CDs, clothing, cameras and household items. Official government data, operational data from a large logistics service provider, face‐to‐face and telephone interviews with company managers and realistic assumptions derived from the literature form the basis of the calculations. Allowance has been made for home delivery failures, “browsing” trips to the shops and the return of unwanted goods.
Findings
Overall, the research suggests that, while neither home delivery nor conventional shopping has an absolute CO2 advantage, on average, the home delivery operation is likely to generate less CO2 than the typical shopping trip. Nevertheless, CO2 emissions per item for intensive/infrequent shopping trips by bus could match online shopping/home delivery.
Research limitations/implications
The number of items purchased per shopping trip, the choice of travel mode and the willingness to combine shopping with other activities and to group purchases into as few shopping trips or online transactions as possible are shown to be critical factors. Online retailers and home delivery companies could also apply measures (e.g. maximising drop densities and increasing the use of electric vehicles) to enhance the CO2 efficiency of their logistical operations and gain a clearer environmental advantage.
Practical implications
Both consumers and suppliers need to be made more aware of the environmental implications of their respective purchasing behaviour and distribution methods so that potential CO2 savings can be made.
Originality/value
The paper offers insights into the carbon footprints of conventional and online retailing from a “last mile” perspective.
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Surajit Bag, Gautam Srivastava, Md Mamoon Al Bashir, Sushma Kumari, Mihalis Giannakis and Abdul Hannan Chowdhury
The first research objective is to understand the role of digital [artificial intelligence (AI)] technologies on user engagement and conversion that has resulted in high online…
Abstract
Purpose
The first research objective is to understand the role of digital [artificial intelligence (AI)] technologies on user engagement and conversion that has resulted in high online activities and increased online sales in current times in India. In addition, combined with changes such as social distancing and lockdown due to the COVID-19 pandemic, digital disruption has largely impacted the old ways of communication both at the individual and organizational levels, ultimately resulting in prominent social change. While interacting in the virtual world, this change is more noticeable. Therefore, the second research objective is to examine if a satisfying experience during online shopping leads to repurchase intention.
Design/methodology/approach
Using primary data collected from consumers in a developing economy (India), we tested the theoretical model to further extend the theoretical debate in consumer research.
Findings
This study empirically tests and further establishes that deploying AI technologies have a positive relationship with user engagement and conversion. Further, conversion leads to satisfying user experience. Finally, the relationship between satisfying user experience and repurchase intention is also found to be significant.
Originality/value
The uniqueness of this study is that it tests few key relationships related to user engagement during this uncertain period (COVID-19 pandemic) and examines the underlying mechanism which leads to increase in online sales.
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Jitendra Gaur, Kumkum Bharti and Rahul Bajaj
Allocation of the marketing budget has become increasingly challenging due to the diverse channel exposure to customers. This study aims to enhance global marketing knowledge by…
Abstract
Purpose
Allocation of the marketing budget has become increasingly challenging due to the diverse channel exposure to customers. This study aims to enhance global marketing knowledge by introducing an ensemble attribution model to optimize marketing budget allocation for online marketing channels. As empirical research, this study demonstrates the supremacy of the ensemble model over standalone models.
Design/methodology/approach
The transactional data set for car insurance from an Indian insurance aggregator is used in this empirical study. The data set contains information from more than three million platform visitors. A robust ensemble model is created by combining results from two probabilistic models, namely, the Markov chain model and the Shapley value. These results are compared and validated with heuristic models. Also, the performances of online marketing channels and attribution models are evaluated based on the devices used (i.e. desktop vs mobile).
Findings
Channel importance charts for desktop and mobile devices are analyzed to understand the top contributing online marketing channels. Customer relationship management-emailers and Google cost per click a paid advertising is identified as the top two marketing channels for desktop and mobile channels. The research reveals that ensemble model accuracy is better than the standalone model, that is, the Markov chain model and the Shapley value.
Originality/value
To the best of the authors’ knowledge, the current research is the first of its kind to introduce ensemble modeling for solving attribution problems in online marketing. A comparison with heuristic models using different devices (desktop and mobile) offers insights into the results with heuristic models.
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Amy Chan Hyung Kim, James Du and Jeffrey James
The purpose of the current research was to examine the different relationships between individuals' sense of community in sport (SCS) cultivated by participating in local sport…
Abstract
Purpose
The purpose of the current research was to examine the different relationships between individuals' sense of community in sport (SCS) cultivated by participating in local sport leagues, social support and health-related psychological outcomes (i.e. depressive symptoms and happiness) based on the participants' involvement level in the tennis league.
Design/methodology/approach
Using participants (n = 150) from local tennis leagues in the Southeastern region of the USA, the authors first conducted an instrument validation procedure to assess the psychometric properties of the included measures, and second, the authors analyzed the proposed multigroup moderated-mediation structural model using component-based partial least squares structural equation modeling with SmartPLS 3 (Ringle et al., 2015).
Findings
The results provide adequate evidence of reliability and validity for both the included reflective and formative constructs. Further, the findings of the proposed moderated-mediation structural model indicated that SCS was positively and significantly associated with social support and happiness while negatively related with depressive symptoms. Social support only mediated the relationship between SCS and happiness. The multigroup analysis results showed significant differences in the relationship between social support and happiness between the least involved group and more involved groups.
Originality/value
The findings of this study indicated that SCS experienced through participation in local sport leagues can develop both the extent and quality of supportive social relationships with other engaging members. One conclusion from the findings is recognizing a need to develop interventions to enhance SCS, social support and health-related psychological outcomes through local sport league participation.