JD.com: Transaction-Level Data for the 2020 MSOM Data Driven Research Challenge

2020 ◽  
Author(s):  
Max Shen ◽  
Christopher S. Tang ◽  
Di Wu ◽  
Rong Yuan ◽  
Wei Zhou
Keyword(s):  
Econometric Models ◽  
Data Driven ◽  
Level Data ◽  
Research Questions ◽  
Transaction Level ◽  
Research Challenge ◽  
Transactional Data

To support the 2020 MSOM Data Driven Research Challenge, JD.com, China’s largest retailer, offers transaction-level data to MSOM members for conducting data-driven research. This article describes the transactional data associated with over 2.5 million customers (457,298 made purchases) and 31,868 stock keeping units (SKUs) over the month of March in 2018. We also present potential research questions suggested by JD.com. Researchers are welcome to develop econometric models or data-driven models using this database to address some of the suggested questions or examine their own research questions.

JD.com: Transaction Level Data for the 2020 MSOM Data Driven Research Challenge

2019 ◽  
Author(s):  
Zuo-Jun Max Shen ◽  
Christopher S. Tang ◽  
Di Wu ◽  
Rong Yuan ◽  
Wei Zhou
Keyword(s):  
Data Driven ◽  
Level Data ◽  
Transaction Level ◽  
Research Challenge

RiRiShun Logistics: Home Appliance Delivery Data for the 2021 Manufacturing & Service Operations Management Data-Driven Research Challenge

2021 ◽  
Author(s):  
Xiaolong Guo ◽  
Yugang Yu ◽  
Gad Allon ◽  
Meiyan Wang ◽  
Zhentai Zhang
Keyword(s):  
Operations Management ◽  
Service Operations ◽  
Optimization Techniques ◽  
Data Driven ◽  
Analytical Models ◽  
Data Set ◽  
Service Operations Management ◽  
Level Data ◽  
Home Appliance ◽  
Research Challenge

To support the 2021 Manufacturing & Service Operations Management (MSOM) Data-Driven Research Challenge, RiRiShun Logistics (a Haier group subsidiary focusing on logistics service for home appliances) provides MSOM members with logistics operational-level data for data-driven research. This paper provides a detailed description of the data associated with over 14 million orders from 149 clients (the consigners) associated with 4.2 million end consumers (the recipients and end users of the appliances) in China, involving 18,000 stock keeping units operated at 103 warehouses. Researchers are welcomed to develop econometric models, data-driven optimization techniques, analytical models, and algorithm designs by using this data set to address questions suggested by company managers.

What's Happening to Profits at Cazenovia Creations?

2013 ◽  
Vol 8 (1) ◽  
pp. 24-29 ◽  
Author(s):  
Margaret Garnsey ◽  
Andrea Hotaling
Keyword(s):  
Financial Analysis ◽  
Financial Statements ◽  
Internal Controls ◽  
Net Income ◽  
Database Query ◽  
Microsoft Access ◽  
Level Data ◽  
Query Tool ◽  
Transaction Level

ABSTRACT In this case, students assume the role of an accounting professional asked by a client to investigate why net income is not as strong as expected. The students must first analyze a set of financial statements to identify areas of possible concern. After determining the areas to investigate, the students use a database query tool to see if they can determine causes by examining transaction level data. Finally, the students are asked to professionally communicate their findings and recommendations to their client. The case provides students with experience in using query-based approaches to answering business questions. It is appropriate for students with basic query and financial analysis skills and knowledge of internal controls. A Microsoft Access database with transaction details for the final seven months of the current year as well as financial statements for the current and prior year are provided.

Does hotel class moderate the impact of crime on operating performance?

2020 ◽  
pp. 135481662094904
Author(s):  
Yang Yang ◽  
Nan Hua
Keyword(s):  
Operating Performance ◽  
Routine Activities ◽  
Econometric Models ◽  
Routine Activities Theory ◽  
Luxury Hotels ◽  
Level Data ◽  
Local Residents ◽  
The Impact ◽  
Practical Implications ◽  
Theory Framework

Hotel guests are more likely to be targeted by criminals than local residents, and the hotel business is particularly vulnerable to various crimes. This study investigates whether guests prefer to stay at luxury hotels when in insecure neighborhoods to reduce the risk of victimization. Using monthly property-level data from 352 hotels between 2010 and 2014 in Houston, Texas, we estimate a series of econometric models to investigate the impact of crime. Results suggest that hotel class moderates the effect of crime on lodging performance, and high-end hotels are less influenced by crime incidents. For luxury hotels, this effect is further moderated by the lodging market structure of vicinity such that the effect is smaller for luxury hotels in a more concentrated market. Lastly, this study carefully addresses theoretical implications that confirm the routine activities theory framework as well as practical implications that suggest measures and strategies handling various impacts related to crime and hotel class studied herein.

scholarly journals Language change and language evolution: Cousins, siblings, twins?

2020 ◽  
Author(s):  
Stefan Hartmann
Keyword(s):  
Adaptive Systems ◽  
Language Change ◽  
Historical Linguistics ◽  
Language Evolution ◽  
Integrated Approach ◽  
Data Driven ◽  
Historical Time ◽  
Research Questions ◽  
The Relationship ◽  
Cross Fertilization

The relationship between “language change” and “language evolution” has recently become subject to some debate regarding the scope of both concepts. It has been claimed that while the latter used to refer to language origins in the first place, both terms can now, to a certain extent, be used synonymously. In this paper, I argue that this can partly be explained by parallel develop-ments both in historical linguistics and in the field of language evolution research that have led to a considerable amount of convergence between both fields. Both have adopted usage-based approaches and data-driven methods, which entails similar research questions and similar perspectives on the phenomena under investigation. This has ramifications for current models and theories of language change (or evolution). Two approaches in particular – the concept of com-plex adaptive systems and construction grammar – have been combined in integrated approaches that seek to explain both language emergence and language change over historical time. I discuss the potential and limitations of this integrated approach, and I argue that there is still some unex-plored potential for cross-fertilization.

Product-level profitability

2019 ◽  
Vol 33 (1) ◽  
pp. 214-237
Author(s):  
Hannu Hannila ◽  
Joni Koskinen ◽  
Janne Harkonen ◽  
Harri Haapasalo
Keyword(s):  
Business Processes ◽  
Data Driven ◽  
Product Portfolio ◽  
Data Governance ◽  
Content Type ◽  
Technical Product ◽  
Product Level ◽  
Level Data ◽  
Corporate Level

Purpose The purpose of this paper is to analyse current challenges and to articulate the preconditions for data-driven, fact-based product portfolio management (PPM) based on commercial and technical product structures, critical business processes, corporate business IT and company data assets. Here, data assets were classified from a PPM perspective in terms of (product/customer/supplier) master data, transaction data and Internet of Things data. The study also addresses the supporting role of corporate-level data governance. Design/methodology/approach The study combines a literature review and qualitative analysis of empirical data collected from eight international companies of varying size. Findings Companies’ current inability to analyse products effectively based on existing data is surprising. The present findings identify a number of preconditions for data-driven, fact-based PPM, including mutual understanding of company products (to establish a consistent commercial and technical product structure), product classification as strategic, supportive or non-strategic (to link commercial and technical product structures with product strategy) and a holistic, corporate-level data model for adjusting the company’s business IT (to support product portfolio visualisation). Practical implications The findings provide a logical and empirical basis for fact-based, product-level analysis of product profitability and analysis of the product portfolio over the product life cycle, supporting a data-driven approach to the optimisation of commercial and technical product structure, business IT systems and company product strategy. As a virtual representation of reality, the company data model facilitates product visualisation. The findings are of great practical value, as they demonstrate the significance of corporate-level data assets, data governance and business-critical data for managing a company’s products and portfolio. Originality/value The study contributes to the existing literature by specifying the preconditions for data-driven, fact-based PPM as a basis for product-level analysis and decision making, emphasising the role of company data assets and clarifying the links between business processes, information systems and data assets for PPM.

scholarly journals Showcasing the diversity of service research

2017 ◽  
Vol 28 (5) ◽  
pp. 810-836 ◽  
Author(s):  
Sabine Benoit ◽  
Katrin Scherschel ◽  
Zelal Ates ◽  
Linda Nasr ◽  
Jay Kandampully
Keyword(s):  
Service Management ◽  
Service Research ◽  
Firm Level ◽  
Content Type ◽  
Quantitative And Qualitative Research ◽  
Research Journal ◽  
Level Data ◽  
Depth Analysis ◽  
Publication Success ◽  
Transactional Data

Purpose The purpose of this paper is to make two main contributions: first, showcase the diversity of service research in terms of the variety of used theories and methods, and second, explain (post-publication) success of articles operationalized as interest in an article (downloads), usage (citations), and awards (best paper nomination). From there, three sub-contributions are derived: stimulate a dialogue about existing norms and practices in the service field, enable and encourage openness amongst service scholars, and motivate scholars to join the field. Design/methodology/approach A mixed method approach is used in combining quantitative and qualitative research methods while analyzing 158 Journal of Service Management (JOSM) articles on several criteria such as their theory, methodology, and main descriptive elements (e.g. number of authors or references) and then using automated text analysis (e.g. investigating the readability of articles, etc.). Findings The results show that the JOSM publishes a large variety of articles with regard to theories, methods of data collection, and types of data analysis. For example, JOSM has published a mixture of qualitative and quantitative articles and papers containing firm-level and customer-level data. Further, the results show that even though conceptual articles create the same amount of interest (downloads), they are used more (citations). Research limitations/implications This paper presents many descriptive results which do not allow for making inferences toward the entire service research discipline. Further, it is only based on one service research journal (JOSM) through a five-year span of publication. Practical implications The results have a number of implications for the discipline that are presented and discussed. Amongst them are that: the discipline should be more open toward conceptual articles, service research shows an imbalance toward theory testing, there is more potential to work with transactional data, and writing style should be more accessible (i.e. readable). Originality/value This paper is the first to conduct an in-depth analysis of service research articles to stimulate dialogue about common publishing practices in the JOSM and to increase the openness of the field.

scholarly journals Geography of racial coresidence

2021 ◽  
Author(s):  
Anna Dmowska ◽  
Tomasz Stepinski
Keyword(s):  
Metropolitan Areas ◽  
Data Driven ◽  
Racial Groups ◽  
Census Block ◽  
Asian Populations ◽  
Racial Preferences ◽  
Level Data ◽  
Geographical Regions ◽  
Block Level ◽  
Us Cities

Whereas most work on residential race relations in US cities is based on the concept of segregation, our approach studies this issue from a who-lives-with-whom perspective. To this end, we study coresidence profiles – percentages of a given racial subpopulation living in different population zones. Population zones are data-driven divisions of a city based on characteristic racial compositions. We used 1990 and 2010 decennial census block-level data for 61 largest US metropolitan areas to calculate coresidence profiles for four major racial subpopulations in each city at both years. Profiles for each race/year combination were clustered into three archetypes. Cities, where given race profiles belong to the same archetype, have similar coresidence patterns with respect to this race. We present the geographic distributions of co-habitation profiles and show how they changed during the 1990-2010 period. Our results revealed that coresidence profiles depend not only on racial preferences but also on the availability of racial groups; cities in the different geographical regions have different coresidence profiles because they have different shares of White, Black, Hispanic, and Asian subpopulations. Temporal changes in coresidence profiles are linked to the increased share of Hispanic and Asian populations.

Sign in / Sign up

Export Citation Format

Share Document