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Dr. Dilupa Nakandala
School of Business, Western Sydney University, Penrith, NSW 2751, Australia

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0 Innovation Management
0 Project Management
0 Renewable Energy
0 Food supply chain management
0 Technology transfer management

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Food supply chain management

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Earlycite article
Published: 30 April 2021 in Industrial Management & Data Systems
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Purpose In the cold supply chain (SC), effective risk management is regarded as an essential component to address the risky and uncertain SC environment in handling time- and temperature-sensitive products. However, existing multi-criteria decision-making (MCDM) approaches greatly rely on expert opinions for pairwise comparisons. Despite the fact that machine learning models can be customised to conduct pairwise comparisons, it is difficult for small and medium enterprises (SMEs) to intelligently measure the ratings between risk criteria without sufficiently large datasets. Therefore, this paper aims at developing an enterprise-wide solution to identify and assess cold chain risks. Design/methodology/approach A novel federated learning (FL)-enabled multi-criteria risk evaluation system (FMRES) is proposed, which integrates FL and the best–worst method (BWM) to measure firm-level cold chain risks under the suggested risk hierarchical structure. The factors of technologies and equipment, operations, external environment, and personnel and organisation are considered. Furthermore, a case analysis of an e-grocery SC in Australia is conducted to examine the feasibility of the proposed approach. Findings Throughout this study, it is found that embedding the FL mechanism into the MCDM process is effective in acquiring knowledge of pairwise comparisons from experts. A trusted federation in a cold chain network is therefore formulated to identify and assess cold SC risks in a systematic manner. Originality/value A novel hybridisation between horizontal FL and MCDM process is explored, which enhances the autonomy of the MCDM approaches to evaluate cold chain risks under the structured hierarchy.

ACS Style

Henry Lau; Yung Po Tsang; Dilupa Nakandala; Carman K.M. Lee. Risk quantification in cold chain management: a federated learning-enabled multi-criteria decision-making methodology. Industrial Management & Data Systems 2021, 121, 1684 -1703.

AMA Style

Henry Lau, Yung Po Tsang, Dilupa Nakandala, Carman K.M. Lee. Risk quantification in cold chain management: a federated learning-enabled multi-criteria decision-making methodology. Industrial Management & Data Systems. 2021; 121 (7):1684-1703.

Chicago/Turabian Style

Henry Lau; Yung Po Tsang; Dilupa Nakandala; Carman K.M. Lee. 2021. "Risk quantification in cold chain management: a federated learning-enabled multi-criteria decision-making methodology." Industrial Management & Data Systems 121, no. 7: 1684-1703.

Empirical article
Published: 24 January 2020 in Service Business
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Drawing upon the ambidextrous leadership theory for innovation, this study investigates the role of opening and closing leadership behaviors in both exploratory and exploitative learning in teams, and subsequently, in team innovation in the context of retail services. Results based on a survey data set collected from 296 team leaders in retail services in two major cities in Vietnam show that opening leadership behavior positively affects team exploratory learning and closing leadership behavior underlies team exploitative learning. Further, the interaction between opening and closing leadership behaviors positively affects both team exploratory and exploitative learning. Finally, these two types of team learning enhance team innovation. Our findings extend the existing literature on ambidextrous leadership, learning, and innovation to the team level in a transitioning economy and suggest possible ways for team leaders to enhance team innovation performance.

ACS Style

La Anh Duc; Nguyen Dinh Tho; Dilupa Nakandala; Yi-Chen Lan. Team innovation in retail services: the role of ambidextrous leadership and team learning. Service Business 2020, 14, 167 -186.

AMA Style

La Anh Duc, Nguyen Dinh Tho, Dilupa Nakandala, Yi-Chen Lan. Team innovation in retail services: the role of ambidextrous leadership and team learning. Service Business. 2020; 14 (1):167-186.

Chicago/Turabian Style

La Anh Duc; Nguyen Dinh Tho; Dilupa Nakandala; Yi-Chen Lan. 2020. "Team innovation in retail services: the role of ambidextrous leadership and team learning." Service Business 14, no. 1: 167-186.

Earlycite article
Published: 06 January 2020 in British Food Journal
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Purpose The purpose of this paper is to investigate supply chain relationships in an urban local fresh food system from a retailer perspective to examine the types of relationships and the factors underpinning the development of such relationships. Design/methodology/approach Using the multiple case study method, interview data from twelve urban local fresh food retailers in Sydney were analysed using the thematic analysis. Findings This study finds that balanced power relationships in the supply chain allow reasonable power to sit with growers in product price determination irrespective of the dependency of small-scale growers on relatively large local retailers. Trust-based relationships are developed over multiple transactions, where shared values across the supply chain and consistently low opportunistic behaviour in reward sharing are demonstrated to be the crucial factors underpinning close relationships. This study also found evidence of horizontal supply chain linkages among retailers in a competitive environment. Practical implications Findings of this study have implications for policymakers in designing urban fresh food systems and for practitioners in large urban retailers including supermarkets that attempt to integrate local food into their product portfolio. Originality/value This study extends the local food system literature dominated by rural studies to include new knowledge about the dynamics of collaborations in contemporary urban local fresh food supply chains. It provides the first empirical evidence of lateral inventory transshipment between retailers in a competitive environment confirming previous simulation studies.

ACS Style

Dilupa Nakandala; Meg Smith; Henry Lau. Shared power and fairness in trust-based supply chain relationships in an urban local food system. British Food Journal 2020, 122, 870 -883.

AMA Style

Dilupa Nakandala, Meg Smith, Henry Lau. Shared power and fairness in trust-based supply chain relationships in an urban local food system. British Food Journal. 2020; 122 (3):870-883.

Chicago/Turabian Style

Dilupa Nakandala; Meg Smith; Henry Lau. 2020. "Shared power and fairness in trust-based supply chain relationships in an urban local food system." British Food Journal 122, no. 3: 870-883.

Journal article
Published: 11 March 2019 in Supply Chain Management: An International Journal
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PurposeThis paper aims to investigate the characteristics of demand and supply in relation to the real-world supply chain strategies of local urban fresh food supply chains (FFSC). It generates insights into how a range of strategies is adopted by urban retailer businesses in attempting to cater for the particular requirements of food-literate urban consumers and small-scale local growers.Design/methodology/approachUsing a multiple case study method, 12 urban local fresh food retailers in Sydney were studied and interview data were analyzed using thematic analysis.FindingsLocal fresh produce has characteristics of both functional and innovative products. Retailers with strong upstream and downstream collaborations adopt hybrid strategies for increased time efficiency and product variety. The dominance of strategies for time efficiency in downstream activities is aimed at maximising the product’s freshness and taste, while product range improvement strategies mean innovative retailers are working with growers to introduce new product types and offering new recipes to consumers that encourage a wider use of products. Urban retailers of local fresh produce leverage on their relationships with upstream and downstream supply chain entities in implementing hybrid strategies.ImplicationsPolicymakers will make use of the new knowledge generated about the real enablers of contemporary urban food systems in designing developmental policies; findings will inform urban FFSC retailers about how harmonious relationships can be leveraged for sustainability.Originality/valueThe study generates new knowledge on the implementation of a leagile approach by studying the adoption of innovative hybrid strategies by urban local FFSCs in relations to demand and supply characteristics and the utilization of strong vertical relationships in a short supply chain.

ACS Style

Dilupa Nakandala; H.C.W. Lau. Innovative adoption of hybrid supply chain strategies in urban local fresh food supply chain. Supply Chain Management: An International Journal 2019, 24, 241 -255.

AMA Style

Dilupa Nakandala, H.C.W. Lau. Innovative adoption of hybrid supply chain strategies in urban local fresh food supply chain. Supply Chain Management: An International Journal. 2019; 24 (2):241-255.

Chicago/Turabian Style

Dilupa Nakandala; H.C.W. Lau. 2019. "Innovative adoption of hybrid supply chain strategies in urban local fresh food supply chain." Supply Chain Management: An International Journal 24, no. 2: 241-255.

Journal article
Published: 03 August 2018 in Industrial Management & Data Systems
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Purpose The purpose of this paper is to propose an outcome-based process optimization model which can be deployed in companies to enhance their business operations, strengthening their competitiveness in the current industrial environment. To validate the approach, a case example has been included to assess the practicality and validity of this approach to be applied in actual environment. Design/methodology/approach This model embraces two approaches including: fuzzy logic for mimicking the human thinking and decision making mechanism; and data mining association rules approach for optimizing the analyzed knowledge for future decision-making as well as providing a mechanism to apply the obtained knowledge to support the improvement of different types of processes. Findings The new methodology of the proposed algorithm has been evaluated in a case study and the algorithm shows its potential to determine the primary factors that have a great effect upon the final result of the entire operation comprising a number of processes. In this case example, relevant process parameters have been identified as the important factors causing significant impact on the result of final outcome. Research limitations/implications The proposed methodology requires the dependence on human knowledge and personal experience to determine the various fuzzy regions of the processes. This can be fairly subjective and even biased. As such, it is advisable that the development of artificial intelligence techniques to support automatic machine learning to derive the fuzzy sets should be promoted to provide more reliable results. Originality/value Recent study on the relevant topics indicates that an intelligent process optimization approach, which is able to interact seamlessly with the knowledge-based system and extract useful information for process improvement, is still seen as an area that requires more study and investigation. In this research, the process optimization system with an effective process mining algorithm embedded for supporting knowledge discovery is proposed for use to achieve better quality control.

ACS Style

Henry Lau; C.K.M. Lee; Dilupa Nakandala; Paul Shum. An outcome-based process optimization model using fuzzy-based association rules. Industrial Management & Data Systems 2018, 118, 1138 -1152.

AMA Style

Henry Lau, C.K.M. Lee, Dilupa Nakandala, Paul Shum. An outcome-based process optimization model using fuzzy-based association rules. Industrial Management & Data Systems. 2018; 118 (6):1138-1152.

Chicago/Turabian Style

Henry Lau; C.K.M. Lee; Dilupa Nakandala; Paul Shum. 2018. "An outcome-based process optimization model using fuzzy-based association rules." Industrial Management & Data Systems 118, no. 6: 1138-1152.

Original article
Published: 11 June 2018 in Expert Systems
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With the increasing use of emergency departments, many public hospitals experience bottlenecks that hinder patient flow within the health system. Mitigating bottlenecks can enhance workflow efficiency and reduce patient wait‐time. Yet given the complexity of health services, current techniques have a limited capacity to address this issue. This article introduces an innovative generic cost‐optimization model based on genetic algorithm to alleviate bottlenecks without the need for complex mathematical analysis. A case study is presented to validate its feasibility, demonstrating an evidence‐based, pragmatic way to alleviate bottlenecks that practitioners can readily implement.

ACS Style

Henry Lau; Ann Dadich; Dilupa Nakandala; Huntley Evans; Li Zhao. Development of a cost-optimization model to reduce bottlenecks: A health service case study. Expert Systems 2018, 35, e12294 .

AMA Style

Henry Lau, Ann Dadich, Dilupa Nakandala, Huntley Evans, Li Zhao. Development of a cost-optimization model to reduce bottlenecks: A health service case study. Expert Systems. 2018; 35 (6):e12294.

Chicago/Turabian Style

Henry Lau; Ann Dadich; Dilupa Nakandala; Huntley Evans; Li Zhao. 2018. "Development of a cost-optimization model to reduce bottlenecks: A health service case study." Expert Systems 35, no. 6: e12294.

Original articles
Published: 30 January 2018 in Enterprise Information Systems
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For enterprises, it is imperative that the trade-off between the cost of inventory and risk implications is managed in the most efficient manner. To explore this, we use the common example of a wholesaler operating in an environment where suppliers demonstrate heterogeneous reliability. The wholesaler has partial orders with dual suppliers and uses lateral transshipments. While supplier reliability is a key concern in inventory management, reliable suppliers are more expensive and investment in strategic approaches that improve supplier performance carries a high cost. Here we consider the operational strategy of dual sourcing with reliable and unreliable suppliers and model the total inventory cost where the likely scenario lead-time of the unreliable suppliers extends beyond the scheduling period. We then develop a Customized Integer Programming Optimization Model to determine the optimum size of partial orders with multiple suppliers. In addition to the objective of total cost optimization, this study takes into account the volatility of the cost associated with the uncertainty of an inventory system.

ACS Style

Dilupa Nakandala; Henry Lau; Jingjing Zhang; Angappa Gunasekaran. A pragmatic decision model for inventory management with heterogeneous suppliers. Enterprise Information Systems 2018, 12, 603 -619.

AMA Style

Dilupa Nakandala, Henry Lau, Jingjing Zhang, Angappa Gunasekaran. A pragmatic decision model for inventory management with heterogeneous suppliers. Enterprise Information Systems. 2018; 12 (5):603-619.

Chicago/Turabian Style

Dilupa Nakandala; Henry Lau; Jingjing Zhang; Angappa Gunasekaran. 2018. "A pragmatic decision model for inventory management with heterogeneous suppliers." Enterprise Information Systems 12, no. 5: 603-619.

Journal article
Published: 11 September 2017 in Industrial Management & Data Systems
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Logistics practitioners must continually improve inventory management processes as they daily respond to the twin drivers of customer satisfaction and cost efficiency. The purpose of this paper is to investigate the scenario of sourcing goods through lateral transshipments in a periodic-review policy setting, against a backdrop of cost optimization objectives. The authors develop decision rules that make cost-optimized selection between backordering and combined reactive and proactive lateral transshipment options possible. This necessarily takes account of the trade-off between purchasing, holding and backorder cost components. In addition, the authors use simulation studies to illustrate the superior performance of the proposed decision options. According to results of the simulation studies, the proposed two-step decision rule generates the lower inventory cost than the alternative decisions rules. The outperformance of proposed two-step decision rule is valid in different scenario. This study develops the decision rules to assist wholesaler logistics practitioners to make optimized decisions with regard to whether they should proactively lateral transshipments and if selected, the optimum size of the extra lateral transshipment. This study has made a significant contribution to the existing knowledge base as it develops decision rules for a combined proactive and reactive approach using lateral transhipments to meet both urgent demand and a part of the demand expected during the supplier lead time in a cost-efficient way.

ACS Style

Dilupa Nakandala; Henry Lau; Jingjing Zhang. Strategic hybrid lateral transshipment for cost-optimized inventory management. Industrial Management & Data Systems 2017, 117, 1632 -1649.

AMA Style

Dilupa Nakandala, Henry Lau, Jingjing Zhang. Strategic hybrid lateral transshipment for cost-optimized inventory management. Industrial Management & Data Systems. 2017; 117 (8):1632-1649.

Chicago/Turabian Style

Dilupa Nakandala; Henry Lau; Jingjing Zhang. 2017. "Strategic hybrid lateral transshipment for cost-optimized inventory management." Industrial Management & Data Systems 117, no. 8: 1632-1649.

Journal article
Published: 03 February 2017 in Business Process Management Journal
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Purpose Despite much research on supply chain (SC) integration and the growing emphasis on recent information technology advancements as an enabler of improved performance, there has been limited research focussed specifically on information integration in supply chains (SCs). The purpose of this paper is to systematically review the literature on information integration in the fresh food supply chain (FFSC) from a holistic perspective. Design/methodology/approach Literature review is done by systematically collecting and analysing the recent literature to identify various participant entities of the FFSC information network and their specific information needs. Findings The information needs of FFSC entities are diverse but the needs are common across multiple entities. Research limitations/implications This study only reviewed the FFSC-related literature; an extended study of the food industry may reveal a more comprehensive view. Practical implications These findings are useful for practitioners in understanding the participant entities in the information network and their information needs and for policymakers in formulating FFSC development initiatives. Originality/value The authors are not aware of another study that investigates the FFSC in a holistic approach, one that identifies the actors, their interactions and information needs.

ACS Style

Dilupa Nakandala; Premaratne Samaranayake; Henry Lau; Krishnamurthy Ramanathan. Modelling information flow and sharing matrix for fresh food supply chains. Business Process Management Journal 2017, 23, 108 -129.

AMA Style

Dilupa Nakandala, Premaratne Samaranayake, Henry Lau, Krishnamurthy Ramanathan. Modelling information flow and sharing matrix for fresh food supply chains. Business Process Management Journal. 2017; 23 (1):108-129.

Chicago/Turabian Style

Dilupa Nakandala; Premaratne Samaranayake; Henry Lau; Krishnamurthy Ramanathan. 2017. "Modelling information flow and sharing matrix for fresh food supply chains." Business Process Management Journal 23, no. 1: 108-129.

Original articles
Published: 09 January 2017 in International Journal of Production Research
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Since inventory costs account for half of logistics costs, optimal inventory management to minimise total inventory costs remains a sustainable competitive advantage. Lateral transshipment (LT) is evidently a proven strategy to minimise total inventory costs. The additional LT costs are more than compensated by lowering the stock-out costs. Previous LT models have not been applied to perishable products. Our proposed LT model embodies spoilage costs in the total inventory costs function with the other cost components (purchase from a regular supplier, LT, backordering and holding), and optimises the trade-off among these five key cost components. Numerical examples from a supermarket chain case study demonstrate that, as compared against the no or lower spoilage costs scenarios, lower LT costs are required to trigger the decision point for implementing LT in the higher spoilage costs scenario. However, common to both the with and without spoilage costs scenarios, LT is still the preferred strategy to minimise total inventory costs, given the decision rules are satisfied.

ACS Style

Dilupa Nakandala; Henry Lau; Paul K.C. Shum. A lateral transshipment model for perishable inventory management. International Journal of Production Research 2017, 55, 5341 -5354.

AMA Style

Dilupa Nakandala, Henry Lau, Paul K.C. Shum. A lateral transshipment model for perishable inventory management. International Journal of Production Research. 2017; 55 (18):5341-5354.

Chicago/Turabian Style

Dilupa Nakandala; Henry Lau; Paul K.C. Shum. 2017. "A lateral transshipment model for perishable inventory management." International Journal of Production Research 55, no. 18: 5341-5354.

Journal article
Published: 30 December 2016 in Journal of Information Systems and Technology Management
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There has been an increasing public demand for passenger rail service in the recent times leading to a strong focus on the need for effective and efficient use of resources and managing the increasing passenger requirements, service reliability and variability by the railway management. Whilst shortening the passengers’ waiting and travelling time is important for commuter satisfaction, lowering operational costs is equally important for railway management. Hence, effective and cost optimised train scheduling based on the dynamic passenger demand is one of the main issues for passenger railway management. Although the passenger railway scheduling problem has received attention in operations research in recent years, there is limited literature investigating the adoption of practical approaches that capitalize on the merits of mathematical modeling and search algorithms for effective cost optimization. This paper develops a hybrid fuzzy logic based genetic algorithm model to solve the multi-objective passenger railway scheduling problem aiming to optimize total operational costs at a satisfactory level of customer service. This hybrid approach integrates genetic algorithm with the fuzzy logic approach which uses the fuzzy controller to determine the crossover rate and mutation rate in genetic algorithm approach in the optimization process. The numerical study demonstrates the improvement of the proposed hybrid approach, and the fuzzy genetic algorithm has demonstrated its effectiveness to generate better results than standard genetic algorithm and other traditional heuristic approaches, such as simulated annealing.

ACS Style

Arminda Guerra Lopes; H.C.W Lau; Dilupa Nakandala; Li Zhao. Using Research Methods in Human Computer Interaction to Design Technology for Resilience. Journal of Information Systems and Technology Management 2016, 13, 505 -524.

AMA Style

Arminda Guerra Lopes, H.C.W Lau, Dilupa Nakandala, Li Zhao. Using Research Methods in Human Computer Interaction to Design Technology for Resilience. Journal of Information Systems and Technology Management. 2016; 13 (3):505-524.

Chicago/Turabian Style

Arminda Guerra Lopes; H.C.W Lau; Dilupa Nakandala; Li Zhao. 2016. "Using Research Methods in Human Computer Interaction to Design Technology for Resilience." Journal of Information Systems and Technology Management 13, no. 3: 505-524.

Journal article
Published: 09 August 2016 in International Journal of Production Research
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Supply chain managers and scholars recognise the importance of managing supply chain risk, especially in fresh food supply chain due to the perishable nature and short life cycle of products. Supply chain risk management consists of supply chain risk assessment, risk evaluation and formulation and implementation of effective risk response strategies. The commonly adopted qualitative methods such as risk assessment matrix to determine the level of risk have limitations. This paper proposes a hybrid model comprising both fuzzy logic (FL) and hierarchical holographic modelling (HHM) techniques where risk is first identified by the HHM method and then assessed using both qualitative risk assessment model (named risk filtering, ranking and management Framework) and fuzzy-based risk assessment method (named FL approach). The risk assessment results by the two different approaches are compared, and the overall risk level of each risk is calculated using the Root Mean Square calculation before identifying response strategies. This novel approach takes advantage of the benefits of both techniques and offsets their drawbacks in certain aspects. A case study in a fresh food supply chain company has been conducted in order to validate the proposed integrated approach on the feasibility of its functionality in a real environment.

ACS Style

Dilupa Nakandala; Henry Lau; Li Zhao. Development of a hybrid fresh food supply chain risk assessment model. International Journal of Production Research 2016, 55, 4180 -4195.

AMA Style

Dilupa Nakandala, Henry Lau, Li Zhao. Development of a hybrid fresh food supply chain risk assessment model. International Journal of Production Research. 2016; 55 (14):4180-4195.

Chicago/Turabian Style

Dilupa Nakandala; Henry Lau; Li Zhao. 2016. "Development of a hybrid fresh food supply chain risk assessment model." International Journal of Production Research 55, no. 14: 4180-4195.

Journal article
Published: 11 July 2016 in Industrial Management & Data Systems
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Purpose – Strategic analysis of customer profitability for assessing market segmentation and reconfiguring customer relationship management (CRM) activities remains the key factor for achieving high return on CRM investment. The purpose of this paper is to map the profit-based ranking of corporate customers into the current market segments, with a view of determining the relative profitability of each market segment. Design/methodology/approach – This study develops a novel model that combines activity-based costing (ABC), CRM, fuzzy analytic hierarchy process (AHP), and technique for order preference by similarity to ideal solution (TOPSIS) methods to evaluate strategically customer profitability and prioritizing corporate accounts. This case study airline company has invested heavily in CRM over the past seven years on integrating multi-functional departments that touch customers. The airline operations management and marketing functions provide key inputs. Results of the hybrid model validate feasibility of the proposed model. Findings – The airline management makes use of the ranking results to optimize customer profitability by reconfiguring marketing programs, integrated schedule design, fleet assignment, maintenance routing, crew scheduling, and real-time optimization of schedule recovery in the aftermath of disruptions or irregularities. The proposed model also directs the marketing function to customize service offerings and introduce appropriate service levels to engage customers of different segments for the purpose of maximizing corporate profitability. Research limitations/implications – Significant amount of investment is necessary to design and implement the extensive CRM database and systems to assure customer data quality and availability so as to bear fruits in the proposed hybrid model. These data requirements can especially be a critical barrier for small to medium-sized companies. Practical implications – This hybrid model is able to capitalize on the benefits of the ABC, CRM, fuzzy AHP, and TOPSIS methods and offset their deficiencies. Most importantly, it can be applied to various industries without complex modification. Originality/value – This study represents the first move to adopt the fuzzy AHP and TOPSIS methods to analyze the ABC and CRM data inputs of an airline company. In mapping the profit-based ranking of corporate customers into the current market segments, the relative profitability of each market segment can be determined.

ACS Style

Henry Lau; Dilupa Nakandala; Premaratne Samaranayake; Paul Shum. A hybrid multi-criteria decision model for supporting customer-focused profitability analysis. Industrial Management & Data Systems 2016, 116, 1105 -1130.

AMA Style

Henry Lau, Dilupa Nakandala, Premaratne Samaranayake, Paul Shum. A hybrid multi-criteria decision model for supporting customer-focused profitability analysis. Industrial Management & Data Systems. 2016; 116 (6):1105-1130.

Chicago/Turabian Style

Henry Lau; Dilupa Nakandala; Premaratne Samaranayake; Paul Shum. 2016. "A hybrid multi-criteria decision model for supporting customer-focused profitability analysis." Industrial Management & Data Systems 116, no. 6: 1105-1130.

Journal article
Published: 04 July 2016 in Business Process Management Journal
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Purpose – When making sourcing decisions, both cost optimization and customer demand fulfillment are equally important for firm competitiveness. The purpose of this paper is to develop a stochastic search technique, hybrid genetic algorithm (HGA), for cost-optimized decision making in wholesaler inventory management in a supply chain network of wholesalers, retailers and suppliers. Design/methodology/approach – This study develops a HGA by using a mixture of greedy-based and randomly generated solutions in the initial population and a local search method (hill climbing) applied to individuals selected for performing crossover before crossover is implemented and to the best individual in the population at the end of HGA as well as gene slice and integration. Findings – The application of the proposed HGA is illustrated by considering multiple scenarios and comparing with the other commonly adopted methods of standard genetic algorithm, simulated annealing and tabu search. The simulation results demonstrate the capability of the proposed approach in producing more effective solutions. Practical implications – The pragmatic importance of this method is for the inventory management of wholesaler operations and this can be scalable to address real contexts with multiple wholesalers and multiple suppliers with variable lead times. Originality/value – The proposed stochastic-based search techniques have the capability in producing good-quality optimal or suboptimal solutions for large-scale problems within a reasonable time using ordinary computing resources available in firms.

ACS Style

Dilupa Nakandala; Henry Lau; Andrew Ning. A hybrid approach for cost-optimized lateral transshipment in a supply chain environment. Business Process Management Journal 2016, 22, 860 -878.

AMA Style

Dilupa Nakandala, Henry Lau, Andrew Ning. A hybrid approach for cost-optimized lateral transshipment in a supply chain environment. Business Process Management Journal. 2016; 22 (4):860-878.

Chicago/Turabian Style

Dilupa Nakandala; Henry Lau; Andrew Ning. 2016. "A hybrid approach for cost-optimized lateral transshipment in a supply chain environment." Business Process Management Journal 22, no. 4: 860-878.

Journal article
Published: 11 April 2016 in Industrial Management & Data Systems
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Purpose – All along the length of the supply chain, fresh food firms face the challenge of managing both product quality, due to the perishable nature of the products, and product cost. The purpose of this paper to develop a method to assist logistics managers upstream in the fresh food supply chain in making cost optimized decisions regarding transportation, with the objective of minimizing the total cost while maintaining the quality of food products above acceptable levels. Design/methodology/approach – Considering the case of multiple fresh food products collected from multiple farms being transported to a warehouse or a retailer, this study develops a total cost model that includes various costs incurred during transportation. The practical application of the model is illustrated by using several computational intelligence approaches including genetic algorithms (GA), fuzzy genetic algorithms (FGA) as well as an improved simulated annealing (SA) procedure applied with a repair mechanism for efficiency benchmarking. The authors demonstrate the practical viability of these approaches by using a simulation study based on pertinent data and evaluate the simulation outcomes. Findings – The application of the proposed total cost model was demonstrated using three approaches of GA, FGA and SA with a repair mechanism. All three approaches are adoptable; however, based on the performance evaluation, it was evident that the FGA is more likely to produce a better performance than the other two approaches of GA and SA. Practical implications – This study provides a pragmatic approach for supporting logistics and supply chain practitioners in fresh food industry in making important decisions on the arrangements and procedures related to the transportation of multiple fresh food products to a warehouse from multiple farms in a cost-effective way without compromising product quality. Originality/value – This study extends the literature on cold supply chain management by investigating cost and quality optimization in a multi-product scenario from farms to a retailer and, minimizing cost by managing the quality above expected quality levels at delivery. The scalability of the proposed generic function enables the application to alternative situations in practice such as different storage environments and transportation conditions, etc.

ACS Style

Dilupa Nakandala; Henry Lau; Jingjing Zhang. Cost-optimization modelling for fresh food quality and transportation. Industrial Management & Data Systems 2016, 116, 564 -583.

AMA Style

Dilupa Nakandala, Henry Lau, Jingjing Zhang. Cost-optimization modelling for fresh food quality and transportation. Industrial Management & Data Systems. 2016; 116 (3):564-583.

Chicago/Turabian Style

Dilupa Nakandala; Henry Lau; Jingjing Zhang. 2016. "Cost-optimization modelling for fresh food quality and transportation." Industrial Management & Data Systems 116, no. 3: 564-583.

Journal article
Published: 05 February 2016 in Business Process Management Journal
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Purpose – As a response to increasing global market competition, companies in various industries tend to identify and manage customer relationship to increase profit performance. Companies commit more resources to identify their VIP customers and retain them by all means. The purpose of this paper is to develop a customer relationship management (CRM) business process management (BPM) model to identify airline customers with different degree of relationship and profit potential, and select the highly profitable customers for developing retention strategy and processes, and convert the less profitable into profitable corporate accounts. Design/methodology/approach – This study innovatively apply the well-known techniques including CRM and relationship marketing models, fuzzy analytic hierarchy process (FAHP), and technique for order preference by similarity to ideal solution (TOPSIS) in the BPM research. This novel approach analyzes longer term customer profit and value potential, and prioritizes corporate accounts as the basis for setting appropriate customer service levels and improving the CRM process. This hybrid model is able to capitalize on the benefits of these methods and offset their deficiencies. Most importantly, it can be customized to various industries without complex modification. Findings – This study uses data of an airline company to validate feasibility of the proposed CRM BPM model. The results indicate that this model is able to classify the customers based on various criteria and sub-criteria, thus allowing companies to introduce appropriate service levels to deal with different categories of customers, and improve CRM process so as to maximize customer profit and value potential. Practical implications – This CRM BPM model and analysis provide managers extensive customer knowledge, more analytical and fact-based decision-making support, and a stronger focus on return on investment in sales and marketing. Knowing the profit and value potential generated by individual corporate customer makes it easier to establish the link between the CRM and the profit outcome. This model also benefits the organization and its stakeholders by allocating more resources to the targeted customer relationships that are profitable or valuable, and makes marketing more accountable in its marketing programs. Originality/value – This study makes the first move to innovatively apply the well-known techniques including CRM and relationship marketing models, FAHP, and TOPSIS in the BPM research.

ACS Style

Henry Lau; Dilupa Nakandala; Premaratne Samaranayake; Paul Shum. BPM for supporting customer relationship and profit decision. Business Process Management Journal 2016, 22, 231 -255.

AMA Style

Henry Lau, Dilupa Nakandala, Premaratne Samaranayake, Paul Shum. BPM for supporting customer relationship and profit decision. Business Process Management Journal. 2016; 22 (1):231-255.

Chicago/Turabian Style

Henry Lau; Dilupa Nakandala; Premaratne Samaranayake; Paul Shum. 2016. "BPM for supporting customer relationship and profit decision." Business Process Management Journal 22, no. 1: 231-255.

Journal article
Published: 01 January 2016 in Journal of Information Systems and Technology Management
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There has been an increasing public demand for passenger rail service in the recent times leading to a strong focus on the need for effective and efficient use of resources and managing the increasing passenger requirements, service reliability and variability by the railway management. Whilst shortening the passengers’ waiting and travelling time is important for commuter satisfaction, lowering operational costs is equally important for railway management. Hence, effective and cost optimised train scheduling based on the dynamic passenger demand is one of the main issues for passenger railway management. Although the passenger railway scheduling problem has received attention in operations research in recent years, there is limited literature investigating the adoption of practical approaches that capitalize on the merits of mathematical modeling and search algorithms for effective cost optimization. This paper develops a hybrid fuzzy logic based genetic algorithm model to solve the multi-objective passenger railway scheduling problem aiming to optimize total operational costs at a satisfactory level of customer service. This hybrid approach integrates genetic algorithm with the fuzzy logic approach which uses the fuzzy controller to determine the crossover rate and mutation rate in genetic algorithm approach in the optimization process. The numerical study demonstrates the improvement of the proposed hybrid approach, and the fuzzy genetic algorithm has demonstrated its effectiveness to generate better results than standard genetic algorithm and other traditional heuristic approaches, such as simulated annealing.

ACS Style

H.C.W Lau; Dilupa Nakandala; Li Zhao. Development of a hybrid fuzzy genetic algorithm model for solving transportation scheduling problem. Journal of Information Systems and Technology Management 2016, 12, 505 -524.

AMA Style

H.C.W Lau, Dilupa Nakandala, Li Zhao. Development of a hybrid fuzzy genetic algorithm model for solving transportation scheduling problem. Journal of Information Systems and Technology Management. 2016; 12 (3):505-524.

Chicago/Turabian Style

H.C.W Lau; Dilupa Nakandala; Li Zhao. 2016. "Development of a hybrid fuzzy genetic algorithm model for solving transportation scheduling problem." Journal of Information Systems and Technology Management 12, no. 3: 505-524.

Book chapter
Published: 01 January 2016 in Sustainable and Responsible Entrepreneurship and Key Drivers of Performance
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Genetically Modified (GM) food has been positioned as a significant innovation with a huge potential for alleviating malnutrition in developing economies. Some potential beneficiaries, however, have been reluctant to accept GM food. Many countries have GM food regulations and some have banned GM organisms. This chapter focuses on barriers to diffusion of innovation and analyses the case of GM food diffusion in Sri Lanka using the Rogers's classical model of innovation diffusion. A complete ban on GM products in 2001 was later relaxed to demand only GM labelling regulations, but GM food has not gained a prominent position in the Sri Lankan market. The attributes of GM food perceived by consumers, the communication system, government responses and broader social expectations have been unfavorable to GM food diffusion. The case of GM food innovation in Sri Lanka demonstrates the very social nature of the process, involving far more than seed producers, growers and related commercial enterprises.

ACS Style

Dilupa Nakandala; Tim Turpin. The Barriers to Innovation Diffusion. Sustainable and Responsible Entrepreneurship and Key Drivers of Performance 2016, 186 -203.

AMA Style

Dilupa Nakandala, Tim Turpin. The Barriers to Innovation Diffusion. Sustainable and Responsible Entrepreneurship and Key Drivers of Performance. 2016; ():186-203.

Chicago/Turabian Style

Dilupa Nakandala; Tim Turpin. 2016. "The Barriers to Innovation Diffusion." Sustainable and Responsible Entrepreneurship and Key Drivers of Performance , no. : 186-203.

Journal article
Published: 01 January 2015 in International Journal of Management and Decision Making
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This paper demonstrates how a fuzzy analytic hierarchy process approach can be used to determine technology management strategies for firms in partnerships that result in their sustained technological development. Firms with resource constraints tend to form venture partnerships with technologically advanced partners for indirect strategic benefits. In such partnerships, technology management strategies of host firms need to be manoeuvred strategically as they build local capabilities. Selection of technology management strategy is generally based on subjective judgements that use fuzzy data analysed under multiple decision criteria. Considering the degree of technological contribution from the source firm, technological competency of the host firm, and dominance of the partners as well as the clarity of roles between partners as decision factors, this paper demonstrates how to determine the optimal technology management strategy. The different technological stages of a real firm are analysed in order to illustrate the application of the proposed approach.

ACS Style

Dilupa Nakandala; Henry Lau. A technology management strategy selection method for firms in joint venture partnerships. International Journal of Management and Decision Making 2015, 14, 112 .

AMA Style

Dilupa Nakandala, Henry Lau. A technology management strategy selection method for firms in joint venture partnerships. International Journal of Management and Decision Making. 2015; 14 (2):112.

Chicago/Turabian Style

Dilupa Nakandala; Henry Lau. 2015. "A technology management strategy selection method for firms in joint venture partnerships." International Journal of Management and Decision Making 14, no. 2: 112.

Journal article
Published: 01 January 2015 in International Journal of Services Technology and Management
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Retaining and improving guest loyalty has become the main focus of hospitality management due to fierce competition in recent years. While many existing studies have relied on survey-based methods to assess guest loyalty level, this study aims to achieve precise estimates by using quantitative data and expert knowledge of practitioners. This study proposes a decision support model which integrates fuzzy logic with expert judgment in order to estimate guest loyalty in international tourist hotels, thereby providing strong evidence for further guest loyalty management. This decision support model is illustrated by using a case study of an international tourist hotel. This research provides a rigorous and practical approach that enables hotel managers to estimate and manage guest loyalty. Enhanced knowledge of each guest's loyalty level and the deployment of specific marketing strategies to different guests can help hotels strengthen the existing customer bases more effectively.

ACS Style

Henry C.W. Lau; Dilupa Nakandala; Li Zhao; Ivan K.W. Lai. Using fuzzy logic approach in estimating individual guest loyalty level for international tourist hotels. International Journal of Services Technology and Management 2015, 21, 127 .

AMA Style

Henry C.W. Lau, Dilupa Nakandala, Li Zhao, Ivan K.W. Lai. Using fuzzy logic approach in estimating individual guest loyalty level for international tourist hotels. International Journal of Services Technology and Management. 2015; 21 (1/2/3):127.

Chicago/Turabian Style

Henry C.W. Lau; Dilupa Nakandala; Li Zhao; Ivan K.W. Lai. 2015. "Using fuzzy logic approach in estimating individual guest loyalty level for international tourist hotels." International Journal of Services Technology and Management 21, no. 1/2/3: 127.