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1 – 10 of over 6000Akhilesh Bajaj, Wray Bradley and Li Sun
The purpose of our study is to investigate the impact of corporate culture on sales order backlog.
Abstract
Purpose
The purpose of our study is to investigate the impact of corporate culture on sales order backlog.
Design/methodology/approach
The authors use regression analysis to examine the relation between corporate culture and the level of sales order backlog, an important leading indicator of firm performance.
Findings
Using a large panel sample of US firms for the period of 2003–2021, the authors find a significant and positive relation, suggesting that firms with strong corporate culture have a higher level of sales order backlog.
Originality/value
The study findings contribute to two separate areas of research: corporate culture in management literature and sales order backlog in accounting literature. Prior study has focused on the impact of corporate culture on current firm performance. This study extends prior research by investigating the impact of corporate culture on order backlog, an important leading indicator of future performance.
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Dominic Loske, Tiziana Modica, Matthias Klumpp and Roberto Montemanni
Prior literature has widely established that the design of storage locations impacts order picking task performance. The purpose of this study is to investigate the performance…
Abstract
Purpose
Prior literature has widely established that the design of storage locations impacts order picking task performance. The purpose of this study is to investigate the performance impact of unit loads, e.g. pallets or rolling cages, utilized by pickers to pack products after picking them from storage locations.
Design/methodology/approach
An empirical analysis of archival data on a manual order picking system for deep-freeze products was performed in cooperation with a German brick-and-mortar retailer. The dataset comprises N = 343,259 storage location visits from 17 order pickers. The analysis was also supported by the development and the results of a batch assignment model that takes unit load selection into account.
Findings
The analysis reveals that unit load selection affects order picking task performance. Standardized rolling cages can decrease processing time by up to 8.42% compared to standardized isolated rolling boxes used in cold retail supply chains. Potential cost savings originating from optimal batch assignment range from 1.03% to 39.29%, depending on batch characteristics.
Originality/value
This study contributes to the literature on factors impacting order picking task performance, considering the characteristics of unit loads where products are packed on after they have been picked from the storage locations. In addition, it provides potential task performance improvements in cold retail supply chains.
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Advanced big data analysis and machine learning methods are concurrently used to unleash the value of the data generated by government hotline and help devise intelligent…
Abstract
Purpose
Advanced big data analysis and machine learning methods are concurrently used to unleash the value of the data generated by government hotline and help devise intelligent applications including automated process management, standard construction and more accurate dispatched orders to build high-quality government service platforms as more widely data-driven methods are in the process.
Design/methodology/approach
In this study, based on the influence of the record specifications of texts related to work orders generated by the government hotline, machine learning tools are implemented and compared to optimize classify dispatching tasks by performing exploratory studies on the hotline work order text, including linguistics analysis of text feature processing, new word discovery, text clustering and text classification.
Findings
The complexity of the content of the work order is reduced by applying more standardized writing specifications based on combining text grammar numerical features. So, order dispatch success prediction accuracy rate reaches 89.6 per cent after running the LSTM model.
Originality/value
The proposed method can help improve the current dispatching processes run by the government hotline, better guide staff to standardize the writing format of work orders, improve the accuracy of order dispatching and provide innovative support to the current mechanism.
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Marco Fabio Benaglia, Mei-Hui Chen, Shih-Hao Lu, Kune-Muh Tsai and Shih-Han Hung
This research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature…
Abstract
Purpose
This research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature logistics centers, with the goal of reducing food loss caused by temperature abuse.
Design/methodology/approach
The authors applied ABC clustering to the products in a simulated database of historical orders modeled after the actual order pattern of a large cold logistics company; then, the authors mined the association rules and calculated the sales volume correlation indices of the ordered products. Finally, the authors generated three different simulated order databases to compare order picking time and waiting time of orders in the staging area under eight different storage location assignment strategies.
Findings
All the eight proposed storage location assignment strategies significantly improve the order picking time (by up to 8%) and the waiting time of orders in the staging area (by up to 22%) compared with random placement.
Research limitations/implications
The results of this research are based on a case study and simulated data, which implies that, if the best performing strategies are applied to different environments, the extent of the improvements may vary. Additionally, the authors only considered specific settings in terms of order picker routing, zoning and batching: other settings may lead to different results.
Practical implications
A storage location assignment strategy that adopts dispersion and takes into consideration ABC clustering and shipping frequency provides the best performance in minimizing order picker's travel distance, order picking time, and waiting time of orders in the staging area. Other strategies may be a better fit if the company's objectives differ.
Originality/value
Previous research on optimal storage location assignment rarely considered item association rules based on sales volume correlation. This study combines such rules with several storage planning strategies, ABC clustering, and two warehouse layouts; then, it evaluates their performance compared to the random placement, to find which one minimizes the order picking time and the order waiting time in the staging area, with a 30-min time limit to preserve the integrity of the cold chain. Order picking under these conditions was rarely studied before, because they may be irrelevant when dealing with temperature-insensitive items but become critical in cold warehouses to prevent temperature abuse.
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Hasan Uvet, John Dickens, Jason Anderson, Aaron Glassburner and Christopher A. Boone
This research paper aims to examine two hybrid models of logistics service quality (LSQ) and its influence on satisfaction, loyalty and future purchase intention in a…
Abstract
Purpose
This research paper aims to examine two hybrid models of logistics service quality (LSQ) and its influence on satisfaction, loyalty and future purchase intention in a business-to-consumer (B2C) e-commerce context. This study extends the literature for LSQ by incorporating the second-order assurance quality construct, which comprises personnel contact quality, order discrepancy handling and order returns, into one of the hybrid models.
Design/methodology/approach
A survey-based approach is used to collect data. Participant responses to questions concerning multiple LSQ dimensions and behavioral perceptions from their most recent online shopping experience are measured using structural equation modeling.
Findings
Findings highlight the importance of including a second-order construct assurance quality as a more explanatory model. Results illustrate that online ordering procedures and assurance quality impact customer satisfaction more than other prominent LSQ dimensions. Furthermore, the findings revealed a customer loyalty is a partial mediator between customer satisfaction and future purchase intention. This underscores the significance of improved logistics services as a competitive edge for e-commerce retailers.
Research limitations/implications
Implications are limited to the e-commerce B2C domain.
Practical implications
The findings of this study underscore critical LSQ dimensions that garner greater satisfaction and retention in the online shopping experience. The results indicate that the effective and efficient handling of the initial order and any order problem significantly influences customer satisfaction and reaps the long-term benefits of customer retention.
Originality/value
The authors present and empirically test a hybrid model of LSQ in a B2C e-commerce domain that captures many of the important elements of the customer experience as espoused in the literature.
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Jonas Koreis, Dominic Loske and Matthias Klumpp
Increasing personnel costs and labour shortages have pushed retailers to give increasing attention to their intralogistics operations. We study hybrid order picking systems, in…
Abstract
Purpose
Increasing personnel costs and labour shortages have pushed retailers to give increasing attention to their intralogistics operations. We study hybrid order picking systems, in which humans and robots share work time, workspace and objectives and are in permanent contact. This necessitates a collaboration of humans and their mechanical coworkers (cobots).
Design/methodology/approach
Through a longitudinal case study on individual-level technology adaption, we accompanied a pilot testing of an industrial truck that automatically follows order pickers in their travel direction. Grounded on empirical field research and a unique large-scale data set comprising N = 2,086,260 storage location visits, where N = 57,239 storage location visits were performed in a hybrid setting and N = 2,029,021 in a manual setting, we applied a multilevel model to estimate the impact of this cobot settings on task performance.
Findings
We show that cobot settings can reduce the time required for picking tasks by as much as 33.57%. Furthermore, practical factors such as product weight, pick density and travel distance mitigate this effect, suggesting that cobots are especially beneficial for short-distance orders.
Originality/value
Given that the literature on hybrid order picking systems has primarily applied simulation approaches, the study is among the first to provide empirical evidence from a real-world setting. The results are discussed from the perspective of Industry 5.0 and can prevent managers from making investment decisions into ineffective robotic technology.
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Lin Sun, Chunxia Yu, Jing Li, Qi Yuan and Shaoqiong Zhao
The paper aims to propose an innovative two-stage decision model to address the sustainable-resilient supplier selection and order allocation (SSOA) problem in the single-valued…
Abstract
Purpose
The paper aims to propose an innovative two-stage decision model to address the sustainable-resilient supplier selection and order allocation (SSOA) problem in the single-valued neutrosophic (SVN) environment.
Design/methodology/approach
First, the sustainable and resilient performances of suppliers are evaluated by the proposed integrated SVN-base-criterion method (BCM)-an acronym in Portuguese of interactive and multi-criteria decision-making (TODIM) method, with consideration of the uncertainty in the decision-making process. Then, a novel multi-objective optimization model is formulated, and the best sustainable-resilient order allocation solution is found using the U-NSGA-III algorithm and TOPSIS method. Finally, based on a real-life case in the automotive manufacturing industry, experiments are conducted to demonstrate the application of the proposed two-stage decision model.
Findings
The paper provides an effective decision tool for the SSOA process in an uncertain environment. The proposed SVN-BCM-TODIM approach can effectively handle the uncertainties from the decision-maker’s confidence degree and incomplete decision information and evaluate suppliers’ performance in different dimensions while avoiding the compensatory effect between criteria. Moreover, the proposed order allocation model proposes an original way to improve sustainable-resilient procurement values.
Originality/value
The paper provides a supplier selection process that can effectively integrate sustainability and resilience evaluation in an uncertain environment and develops a sustainable-resilient procurement optimization model.
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Nadira Islam Nila, Jhumana Akter and Md. Mehrab Hossain
Change orders are a typical occurrence in building projects. Change orders indirectly affect labor productivity, resulting in a significant delay in the completion of a building…
Abstract
Purpose
Change orders are a typical occurrence in building projects. Change orders indirectly affect labor productivity, resulting in a significant delay in the completion of a building project. Change orders cause labor productivity losses that are difficult to describe, establish and account for contractors and subcontractors. This study aimed to look at the influence of change orders on labor productivity and develop methods to mitigate their adverse effects.
Design/methodology/approach
To assess the change orders' impact on productivity levels a system dynamic model was developed and devise ways were developed to counteract these negative impacts in this research. The impact of change orders on labor productivity and project time was then controlled using techniques established. Finally, a case study of KUET's hall extension was chosen, and the model and principles developed were implemented.
Findings
This study established that if the project delivery date is set and change orders are occurring often, labor productivity will be impacted. With adequate monitoring and supplemental management techniques, it can be reduced by prolonging the project.
Originality/value
The developed policies aid to mitigate the effect of change orders on labor productivity.
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Manuel Brauch, Matin Mohaghegh and Andreas Größler
One pertinent dynamic phenomenon in supply chains is the amplification of order variance, i.e. the bullwhip effect. Its continued significance is underscored in contemporary…
Abstract
Purpose
One pertinent dynamic phenomenon in supply chains is the amplification of order variance, i.e. the bullwhip effect. Its continued significance is underscored in contemporary empirical research. While numerous publications have pinpointed various causes of the bullwhip effect, there remains a gap in their systematic consolidation. The purpose of this paper is to compile a comprehensive list of the causes of the bullwhip effect from existing literature and categorize them appropriately.
Design/methodology/approach
This study conducts a systematic literature review to offer a comprehensive overview of bullwhip effect causes addressed in the existing literature. The identified causes are categorized using a qualitative content analysis approach.
Findings
The study shows the diversity of the causes of the bullwhip effect and their interdependencies. In addition, this study demonstrates that, at the highest level of aggregation, causes of the bullwhip effect can be classified into four main categories: causes inherent in the system structure, causes related to uncertainty, causes related to misaligned incentives and causes related to inadequate cognition of the situation.
Originality/value
The work provides an extensive overview and categorization of bullwhip effect causes, offering valuable insights for both researchers and practitioners seeking a deeper understanding of this phenomenon. In addition, it underscores managerial implications and highlights future research opportunities.
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John J. Sailors, Jamal A. Al-Khatib, Tarik Khzindar and Shaza Ezzi
The Islamic world spans many different languages with different language structures. This paper aims to explore one way in which language structure affects consumer response to…
Abstract
Purpose
The Islamic world spans many different languages with different language structures. This paper aims to explore one way in which language structure affects consumer response to the marketing of cobrands.
Design/methodology/approach
Two between subject experiments were conducted using samples of participants from Saudi Arabia and the USA. The first manipulated partner brand category similarity and brand name order, along with the structure of the language used to communicate with the market. The data for this study includes Arabic speakers in Saudi Arabia as well as English speakers in the USA. The second study explores how targeting a population fluent in multiple languages of varied structure nullifies the findings from the first study and uses Latino participants in the USA.
Findings
This study finds that when brands come from similar product categories, name order did not affect cobrand evaluations, but it did when the brands come from dissimilar product categories. Here, evaluations of the cobrand are enhanced when the invited brand is in the position that adjectives occupy in the participant’s language. The authors also find that being proficient in two languages, each with a different default order for adjectives and nouns, quashes the effect of name order otherwise seen when brands from dissimilar product categories engage in cobranding.
Originality/value
By examining the impact of language structure on the effects of cobrand evaluation and conducting studies among participants with differing dominant languages, this research can rule out simple primacy or recency effects.
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