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The purpose of this paper is to investigate the effect of residence time distribution in extruders along with the incorporation of nutraceuticals on the final quality of the products with respect to several pivotal responses.

Corn–rice flour blend fortified with isolated nutraceutical concentrates at two (low and high) levels was extruded at barrel temperature (110°C), screw speed (260 rpm) and feed moisture (17 percent). Extrudates were collected at an interval of 24 s followed by analysis for radial expansion (RE), bulk density (BD), water absorption index (WAI), sensory score (SS), textural hardness, colorimetric values (L*, a* and b*) and color difference (E).

The entire data were fitted to zero- and first-order kinetic models. There was a gradual decrease in RE, SS and L* value, whereas an increase in BD, textural hardness and a* value of extrudates fortified with the three nutraceutical concentrates was observed with the successive time interval of 24 s along with a more pronounced effect on color difference (E) observed during the last stages of extrusion time. The zero-order kinetic model was well fitted for BD and a* value, whereas the first-order kinetic model showed better results for RE, WAI, SS, textural hardness, L* value, a* value and b* value of fortified extrudates.

Nutraceuticals like β-glucans, lignans and γ oryzanol exhibit numerous health-beneficial effects. This study analyzes the kinetics of changes in various responses of extrudates fortified with these nutraceutical concentrates during extrusion.

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.

The purpose of this article is to integrate organizational capabilities into the place branding process to showcase how a lead destination marketing organization (DMO) can influence a customer-based brand equity outcome. Doing so highlights the strategic, relational nature of place branding. The authors focus specifically on first- and zero-order capabilities, integrating absorptive capacity (first-order) and an innovation capability (zero-order) into a place branding framework. We define an innovation capability within a place branding context and offer absorptive capacity as a mechanism through which DMO leaders can exploit external knowledge acquisition.

The paper presents a theoretical framework of the place branding process that integrates firm capabilities. A framework based on analyzing existing place branding models and integrating organizational capabilities, which find root in strategic management literature, was developed.

Findings indicate that existing frameworks address operational and customer capabilities in some manner yet largely ignore innovation capabilities. A definition of an innovation capability for place brand managers and scholars is offered, and offer absorptive capacity as means to integrate external knowledge into the DMO. Utilizing multiple levels of capabilities allows a firm to influence customer-based brand equity. Testable propositions based on the authors' framework are offered.

Managerial implications of integrating stakeholder capabilities into place branding include appreciating a culture of innovation within DMOs, learning from external stakeholders meaningfully and regularly and encouraging creative thinking that can produce new processes, policies or services.

By integrating organizational capabilities, attention is drawn to internal aspects of the place branding process the place can control directly. Capabilities dictate how an organization sees itself; learns from its stakeholders; and then integrates that knowledge into organizational, stakeholder and innovation capabilities. Therefore, capabilities are inherently internal mechanisms through which a DMO can influence place brand outcomes, which are understood here as brand equity elements.

The aim of this paper is to deconstruct the organizational capability of ambidexterity into a typology of hierarchical dimensions that includes each type’s enabling mechanisms and capabilities.

This work reviews and integrates extant literature on ambidexterity and the hierarchy of capabilities to distinguish dimensions of ambidexterity and link each type to capabilities identified in prior research.

A hierarchy involving zero-, first- and second-order ambidexterity is developed. Mechanisms and capabilities for creating and sustaining each type of ambidexterity are described.

As only an initial and conceptual foray toward the purpose stated above, this research does not attempt to argue a comprehensive theoretical framework. Nor does it intend to extend or propose new theory regarding the origins of ambidexterity capabilities or the specific causal relationships between them.

Although prior literature emphasizes approaches for achieving and maintaining ambidexterity, these generally refer to what is described here as zero-order ambidexterity. The hierarchical and holistic system view offered in this research suggests greater importance for second-order ambidexterity and capabilities of top managers for exercising cognitive, behavioral and process leadership complexity.

Recent literature on ambidexterity begins to suggest varied types or levels of ambidexterity. No known work, however, has expressly deconstructed ambidexterity into component dimensions via the hierarchy of capabilities framework.

We compare a recently proposed generalized eigensystem approach and a new modified generalized eigensystem approach to more widely used truncated singular value decomposition and zero‐order Tikhonov regularization for solving multidimensional elliptic inverse problems. As a test case, we use a finite element representation of a homogeneous eccentric spheres model of the inverse problem of electrocardiography. Special attention is paid to numerical issues of accuracy, convergence, and robustness. While the new generalized eigensystem methods are substantially more demanding computationally, they exhibit improved accuracy and convergence compared with widely used methods and offer substantially better robustness.

This paper aims to study the color change kinetics of lac dye in response to pH and food spoilage metabolites (ammonia, lactic acid and tyramine) for its potential application in intelligent food packaging.

UV-Vis spectroscopy was used to study the color change of dye solution. Ratio of absorbance of dye solution at 528 nm (peak of ionized form) to absorbance at 488 nm (peak of unionized form) was used to study the color change. Color change kinetics was studied in terms of change in absorbance ratio (A528/A488) with time using zero- and first-order reaction kinetics. An indicator was prepared by incorporating lac dye in agarose membrane to validate the result of study for monitoring quality of raw milk.

Dye was orange-red in acidic medium (pH: 2 to 5) and exhibited absorbance peak at 488 nm. It turned purple in alkaline medium (pH: 7 to10) and exhibited absorbance peak at 528 nm. The change in absorbance ratio with pH followed zero-order model. Acid dissociation constant (pKa) of dye was found to be 6.3. Color change of dye in response to ammonia and tyramine followed zero-order reaction kinetics, whereas for lactic acid, the first-order model was found best. In the validation part, the color of the indicator label changed from purple to orange-red when the milk gets spoiled.

The study opens a new application area for lac dye. The results suggest that lac dye has potential to be used as an indicator in intelligent food packaging for detection of spoilage in seafood, meat, poultry and milk.

Although big data may enhance the visibility, transparency, and responsiveness of supply chains, whether it is effective for improving supply chain performance in a turbulent environment, especially in mitigating the impact of COVID-19, is unclear. The research question the authors addressed is: How do logistics firms improve the supply chain performance in COVID-19 through big data and supply chain integration (SCI)?

The authors used a mixed-method approach with four rounds of data collection. A three-round survey of 323 logistics firms in 26 countries in Europe, America, and Asia was first conducted. The authors then conducted in-depth interviews with 55 logistics firms.

In the first quantitative study, the authors find mediational mechanisms through which big data analytics technology capability (BDATC) and SCI influence supply chain performance. In particular, BDATC and SCI are two second-order capabilities that help firms develop three first-order capabilities (i.e. proactive capabilities, reactive capabilities, and resource reconfiguration) and eventually lead to innovation capability and disaster immunity that allow firms to survive in COVID-19 and improve supply chain performance. The results of the follow-up qualitative analysis not only confirm the inferences from the quantitative analysis but also provide complementary insights into organizational culture and the institutional environment.

The authors contribute to supply chain risk management by developing a three-level hierarchy of capabilities framework and finding a mechanism with the links between big data and big disaster. The authors also provide managerial implications for logistics firms to address the new management challenges posed by COVID-19.

Introduction Operations research, i.e. the application of scientific methodology to operational problems in the search for improved understanding and control, can be said to have started with the application of mathematical tools to military problems of supply bombing and strategy, during the Second World War. Post‐war these tools were applied to business problems, particularly production scheduling, inventory control and physical distribution because of the acute shortages of goods and the numerical aspects of these problems.

The choice of mode of transport used by a shipper to move his goods does not depend solely upon relative transportation costs. It should be viewed as one part of the complex process of deciding the method of distributing a product which, apart from transport, involves materials handling and packaging, inventory control and warehousing and order processing procedures. The transport operator providing a premium system of transport such as air freight may well be able to justify its use if appropriate economies can be obtained from other distribution activities. For example, a shipper would be prepared to incur higher transport costs if he were able to reduce the size of the inventory he had to hold to meet demand. Demonstrating in numerical terms the potential benefits from any changes in the distribution system is a difficult task because of the complexity of inter‐relationships involved. A computer‐based analysis is essential. However, because the results of such analysis must be easily understood it is also necessary that the system employed is simple to use, sparing in its input requirements, with a readily assimilated output: in short, it has to be efficient in the marketing sense, as well as an accurate model of the distribution system.

Addresses important logistical considerations in the distribution of a seasonal food product. While continued attempts have been made to maintain high levels of customer service within the food industry, the degree of uncertainty in the distribution channel itself often undermines management’s efforts to procure adequate stock of product during peak demand season. Develops a stochastic dynamic programming formulation which may serve as a decision‐support tool for managers faced with procuring product in a distribution channel in which receipt quantities are probabilistic. Provides numerical results, supporting the intuitive result that expected costs and the length of the required planning horizon are inversely related to the level of uncertainty in the distribution channel.