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The purpose of the present paper is to provide a comprehensive framework for analyzing relationships among economic actors interconnected through internet and constituting e‐supply networks (e‐SNs).

At first the main factors characterizing e‐SN pattern are identified (organizational structures, managerial criteria and critical activities), then two separate procedures are adopted for developing an integrated reference framework. The first based on the analysis of correlations among variables influencing the factors under investigation; the second based on the analysis of different types of physical and immaterial flows among actors involved in the e‐SN. On the basis of such evidence an integrated global framework is proposed, which is then used to classify and describe some relevant literature‐based case studies.

On the basis of two newly introduced variables, namely the internal integration degree and the decision‐making concentration degree, the framework identifies four sets of organizational structures, managerial criteria and critical activities, each one coherent with specific environmental contexts.

The framework is restricted to describing and classifying different typologies of e‐SN.

The framework may be useful for assessing if the typology of organizational structure, managerial criteria and critical activities adopted for the management of a specific e‐SN, is coherent with e‐SN business environment. It may also provide useful guidelines for managers and practitioners involved in e‐SN design.

The paper provides an original integrated framework to classify e‐SNs.

This study investigates Singaporean millennials’ attitudes toward luxury brands. The research focuses on the financial, functional, individual, and social dimensions of luxury value perception and whether ethnicity influences these dimensions.

The research measures luxury value perception among millennials of the three main ethnic groups in Singapore (Chinese, Indians, and Malays) via more than 200 questionnaires. Data were analyzed through Kruskal-Wallis non-parametric ANOVA and cluster analysis.

Luxury value perception does not vary across ethnicity, with the exception of the financial value dimension. Four market segments of young luxury consumers in Singapore are identified and profiled. These segments do not differ in terms of ethnicity.

Millennials are an evolving and moving population segment, and thus longitudinal analyses would be useful to develop a more comprehensive understanding of this segment.

Ethnicity does not affect luxury value perception. The results of the cluster analysis suggest that luxury companies should address the millennials as a global target sharing the same luxury value perception. At the same time, luxury companies can emphasize some different aspects (i.e., the financial dimension) of their value offer.

The research studies the most interesting market for luxury brands—millennials—in a fast-growing luxury market. It adds knowledge to the previous literature on luxury value perception. This research can guide managers to devise suitable marketing strategies addressing the millennials segment as a global market that has the same set of luxury values worldwide.

Investigates the application of the up‐flow anaerobic sludge bed (UASB) reactor for the anaerobic treatment of sewage sludge containing high concentrations of soluble and insoluble sulphides. Assesses the reactor’s performance in terms of volatile organic matter (VOM) and biogas production rate. The average percentage removal of VOM, total sulphide and biogas for the reactor operation without sulphide was 67 per cent, 65mgS/L and 1 L/day, respectively. The corresponding average percentage removal of VOM, total sulphide and biogas production rate for the experiment with 800mgS/L soluble sulphide was 45 per cent, 450mgS/L and 0.7L/day. Equilibrium concentrations of soluble sulphide up to 200mgS/L exert insignificant toxic effects, but toxicity increases as the concentration of soluble sulphide increases. A concentration of soluble sulphide of 1,200mgS/L produces severe toxic effects and the complete termination of gas production. An inhibitory concentration of sulphides affects gas production first, while significant volatile acid accumulation takes place much slower, and only after gas production has been severely retarded. Insoluble sulphide has an insignificant effect on the UASB up to a concentration of at least 800mgS/L. The addition of iron as ferric chloride prevents the toxicity of soluble sulphides as indicated by the minor effect on gas production. Therefore, the use of iron to precipitate sulphide could be used on a continuous basis to reduce sulphide toxicity.

This study proposes a model for the analysis and performance evaluation of e‐supply chains (e‐SCs), that are supply chains (SCs) in which actors are connected by Internet technologies. It is assumed that e‐SC performances are influenced by the network ol structures, by the criteria adopted to manage relationships among involved actors, and by the critical activities that the leading company performs. At first, the variables influencing such factors are identified and the interdependencies among them are analysed to establish existing correlations. This, in turn, enables one to group the values of the influencing factors in four coherent sets which are consistent with different business environments, thus assuring the effectiveness and efficiency to the e‐SC. The obtained reference model is then tested by applying it to literature‐based case studies. The output of this model may be used to design totally new e‐SCs or to redesign the existing ones, in both manufacturing and services industries.

To present a decision support system (DSS) enabling the analysis of the cost‐effectiveness of direct‐shipping long‐haul road transport policies, including full truck load (FTL) and less than truck load (LTL) modes, and to select the optimal carrier.

Analytical estimation of transportation costs is provided in a framework including an interactive computer procedure and a dedicated database structure capable of characterizing the logistics system.

Main criticalities of manual logistic planning are: sub‐optimal selection of carrier and excessive use of LTL transport, while the optimal FTL vs LTL trade‐off is not fully explored in practice.

This is an analysis tool of user‐defined scenarios and does not provide the automatic synthesis of shipments planning. Admittedly, this model does not attempt to optimize the shipping strategy, but to quantitatively assess the effects of the adopted decisions.

Alternative shipping policies can be compared to perform what‐if analyses and explore the outcome of alternative decisions (FTL vs LTL shipping modes) even in terms of transportation expenditures. Allows rapid selection of the optimal motor carrier and assesses the extra cost due to a sub‐optimal choice. Gives the experienced manager a framework for critical assessment of shipping decisions, suggesting improvement areas for cost reduction.

With respect to other software tools for carrier selection provides explicit analysis of extra costs incurred by manual planning, thus becoming a strategic tool for logistic decision making. Furthermore, enables managerial insights to be gained and makes manual planning more effective.

This purpose of this paper is to present a methodology for optimally planning long‐haul road transport activities through proper aggregation of customer orders in separate full‐truckload or less‐than‐truckload shipments in order to minimize total transportation costs.

The model is applied to a specific Italian multi‐plant firm operating in the plastic film for packaging sector. The method, given the order quantities to be shipped and the location of customers, aggregates shipments in subgroups of compatible orders resorting to a heuristic procedure and successively consolidates them in optimized full truck load and less than truck load shipments resorting to a Genetic Algorithm in order to minimize total shipping costs respecting delivery due dates and proper geographical and truck capacity constraints.

The paper demonstrates that evolutionary computation techniques may be effective in tactical planning of transportation activities. The model shows that substantial savings on overall transportation cost may be achieved adopting the proposed methodology in a real life scenario.

The main limitation of this optimisation methodology is that an heuristic procedure is utilized instead of an enumerative approach in order to at first aggregate shipments in compatible sets before the optimisation algorithm carries out the assignments of customer orders to separate truckloads. Even if this implies that the solution could be sub‐optimal, it has demonstrated a very satisfactory performance and enables the problem to become manageable in real life settings.

The proposed methodology enables to rapidly choose if a customer order should be shipped via a FTL or a LTL transport and performs the aggregation of different orders in separate shipments in order to minimize total transportation costs. As a consequence, the task of logistics managers is greatly simplified and consistently better performances respect manual planning can be obtained.

The described methodology is original in both the kind of approach adopted to solve the problem of optimising orders shipping in long‐haul direct shipping distribution logistics, and in the solution technique adopted which integrates heuristic algorithm and an original formulation of a GA optimisation problem. Moreover, the methodology solves both the truckload assignment problem and the choice of LTL vs FTL shipment thus representing an useful tool for logistics managers.

The best strategy to apply for the future cannot disregard a careful analysis of the past and is the one capable of seizing opportunities from outside. Manufacturing sectors are characterized by sudden changes, and in this work, we analyze the ceramic tiles sector characterized by a mature technology in which innovation has played a key role.

This study aims to provide a sectorial analysis based on a historical data set (2004–2019) to highlight how an industry is performing both operationally and in terms of eco-efficiency. For this purpose, from a methodological point of view, the data envelopment analysis (DEA) was used.

The results of the analysis show that the Spanish ceramics industry shows a growing economic trend by taking advantage of lower industrial costs, while the Italian industry is characterized by a modest decline partially mitigated by exports. The industrial districts are an aggregation of companies that in the ceramic sector has allowed to combine innovation, sustainability and digitalization and is a model toward the maximization of sustainable efficiency because it is a place of aggregation of resources and ideas.

This study experiments with an innovative way of addressing traditional industry analysis, namely, integrating the reflective management approach with DEA-based backward analysis. This provides decision makers with the basis for new interpretations of variable trends.

Logistic strategies represent a key factor to increase supply chain (SC) effectiveness, as the optimization of logistics networks enables transport and storage costs reduction as well as quick response leading to higher customer satisfaction. A useful approach for SC performance improvement may be pursued by resorting to advanced software tools able to analyze complex production scenarios, performing concurrent, synchronized and distributed simulations. Support to the logistics planning phase is offered by geographical information system technology, included in the simulation environment in order to manage related geographical data (i.e. warehouse location, choice of vehicle routeings, etc.). In the paper the main characteristics of the proposed hardware and software architecture have been illustrated, focusing attention on the logic phases for implementation by the transport federate. Furthermore, a preliminary functionality validation of the developed tool is presented with reference to simplified test cases.

Describes the reengineering of a production line for household heating tubular radiators, assuming as a reference scenario the facility of one of the leading Italian manufacturers. After a preliminary characterization of products and manufacturing process, a thorough analysis of the production system has been carried out in order to highlight current problems and improvement strategies in the light of lean manufacturing concepts. Subsequently, suggests some corrective actions and also assesses their expected effectiveness in economic terms. In particular, improvement possibilities have been found in the areas of internal logistics through streamlining of materials flow and layout modifications, as well as process quality increase. Reengineering activities are especially aimed towards layout optimization mainly by resorting to a U‐shaped cell‐based architecture. Further, the reduction of rework percentage during the assembly phase has been pursued by properly modifying the operations sequence and through integration of a new automated testing station in the production line.

The price of extra virgin olive oil (EVOO) is highly subjected to variability. In this way, the consumer is not able to perceive a price of reference. The purpose of this paper is to investigate this topic, trying to define a range suitable for the selling of EVOO.

A mathematical model is applied to the three price levels (i.e. production, intermediate and selling). It studies the relationship among main variables: purchase cost of olives, the production cost of olive oil, the yield of olives obtained by the technological process and the profit margin. To define the input data, 25 producers of olives and 25 owners of olive oil mills are involved.

The production of EVOO depends strictly on the production of olives, which typically is subdivided in a year of “high production” and in a year of “low production.” The price of EVOO is subjected to a great variability; however, it is possible to propose a range that varies from €7.0 per liter to €8.7 per liter.

The level of acidity influences significantly the quality of olive oil, and this model has the limit to not analyze the variation of the price in function of this parameter.

This study is the first to propose a pricing model to evaluate EVOO. The literature section supports this assumption.