Den svenska dagligvaruhandeln kännetecknas av en hög koncentrationsnivå. Fem aktörer – ICA Sverige AB, Coop Sverige AB, Axfood AB, Lidl KB och City Gross AB – har tillsammans en marknadsandel som uppgår till ungefär 98 procent, varav ICAs andel utgör cirka 50 procent. Denna dominans av ett fåtal aktörer inom dagligvaruhandeln blir väldigt tydligt när man befinner sig utanför storstadsområden. I flera kommuner finns exempelvis bara två av de fem största dagligvaruaktörerna etablerade.

Denna rapport har haft till syfte att beskriva andra alternativ till de traditionella etablerade aktörerna och undersöka vilka fördelar och nackdelar de har. Rapporten har fokuserat på alternativa distributionskanaler (ADK) som kan beskrivas som ett nätverk av producenter, konsumenter och andra aktörer som utgör alternativ till de traditionella distributionskanalerna (TDK) för livsmedel. ADK innebär ett mer direkt och skräddarsytt sätt att få maten från jord till bord, vilken skiljer från TDK. Rapporten har initialt definierat och beskrivit begreppet ADK, tittat på olika aktörer och vilka former dessa distributionskanaler tar sig på den svenska livsmedelsmarknaden. Fokus har även varit att undersöka hur dessa aktörer konkurrerar både utifrån ett producent- och konsumentperspektiv.

Förutom att producenter och konsumenter kan hitta nya vägar att nå varandra så är det även viktigt ur ett samhälleligt försörjnings- och beredskapsperspektiv att öka kunskapen om vilka alternativ som finns till den traditionella livsmedelsförsörjningen. Dagens globala och sammankopplade livsmedelssystem är sårbara för extern påverkan, vilket på senare tid har blivit tydligt via Covid-19 pandemin och Ukraina-kriget. För att uppnå den resiliens och självförsörjningsgrad som flera regioner eftersträvar, kan ett komplement till de traditionella distributionskanalerna för livsmedel vara just alternativa former av livsmedelsdistribution.

Inom ramen för denna rapport har det genomförts en genomgång av tillgänglig litteratur inom området samt en studie med intervjuer och enkäter som datainsamlingsverktyg. Den valda geografiska kontexten för fallstudien är Småland och Jönköpings län i Sverige. Genom litteraturstudien framkom det bland annat att den historiska utvecklingen i Sverige har bidragit till att öka andelen och utbudet av ekologiska produkter, koppling till hållbarhet och tekniska innovation inom ADK. Litteraturstudien gav även en bra grund för att utveckla och definiera begrepp relaterade till ADK:er och utveckla en ny typologi för att beskriva dessa ADK:er. Den framtagna typologin av ADK:er är baserat på vilken typ av aktör som är involverade samt hur interaktionen med de centrala aktörerna och konsumenterna sker. Typologin användes sedan för att analysera den data som samlades in.

ADK:er har fördelar över TDK när det gäller att erbjuda lokala varor och tillhandahålla god kvalitet på maten (färskhet). Dessutom bidrar ADK:er till ökade interaktionen mellan livsmedelsproducenten och konsumenter, bättre kontakt med naturen, och att sälja/köpa den historia som följer med produkten. Dock sker majoriteten av konsumenternas köp fortfarande via TDK på grund av kostnad, utbud och bekvämlighet.

De största utmaningarna för ADK:er har under perioden 2018–2023 varit logistik (infrastruktur), energipriser, brist på marknadsföringskanaler och (extrem)väder. Yttre omständligheter som pandemin har påverkat ADK:erna, både positivt och negativt. Konjunkturläget med inflation, i följd av bland annat pandemin och kriget i Ukraina, hade inte gett någon observerbar och betydande påverkan på ADK:erna när rapporten genomfördes. Detta behöver därför undersökas ytterligare och under en längre period, då andra studier, såsom ”Matkronan” visat på en stor påverkan på livsmedelsproducenternas inkomster.

Denna rapport har specifikt undersökt förmågan hos ADK:er att kunna konkurrera med TDK:er för livsmedelsförsörjning i Jönköpingsregionen. Resultaten visar att ADK:er inte konkurrerar på ett avgörande sätt med de etablerade dagligvarukedjorna utan ska mer ses som ett nischat produkt- och försäljningsalternativ för både producenter och konsumenter. Denna rapport ger inte tillräckliga underlag för att kunna dra konkreta slutsatser kring hur förekomsten av ADK påverkar svenska konsumenter men även Sverige på ett mer generellt sätt (exempelvis tillgänglighet till livsmedel). De positiva effekterna är bland annat ökat utbud och efterfrågan på lokala produkter och hemleveranser. 

Manufacturing relocation decisions are complex because they involve combinations of location modes like offshoring or reshoring, and governance modes like insourcing or outsourcing. Furthermore, the uncertainty involved in the decision-making process makes it challenging to reach a right-shoring decision. This study presents a hybrid fuzzy-AHP-TOPSIS model to support generic relocation decisions. Industry experts were involved in a pairwise comparison of the competitive priorities’ decision criteria. A meta-synthesis of empirical studies is used to generate theoretical relocation scenarios. The presented hybrid model is used to rank the relocation scenarios in order to identify the most pertinent alternative. The resiliency of the solution is presented through a sensitivity analysis. The results indicate that the proposed hybrid model can simultaneously handle all the main relocation options involving governance modes. Based on the input data in this study, the competitive priorities criteria quality, time and cost are shown to have a strong impact, whereas the sustainability criterion has a weak impact on the choice of relocation option. The research presented in this paper contributes to the research field of manufacturing relocation by demonstrating the suitability of the hybrid fuzzy-AHP-TOPSIS model for relocation decisions and the resilience of the results. Furthermore, the research contributes to practice by providing managers with a generic relocation decision-support model that is capable of simultaneously handling and evaluating various relocation alternatives.

Reshoring decisions in the manufacturing sector have received increasing attention due to their potential to improve overall quality, flexibility, or reduce risk. Contemporary events such as the pandemic and the supply crisis have made manufacturing reshoring decisions a timely and important topic to study. Particularly, the decision support deserves attention as there is limited knowledge on tools for reshoring decisions. The purpose of this study is to investigate the feasibility of decision support for reshoring decisions. The purpose is addressed through three research questions (RQ). The first question (RQ1) is “What criteria should be considered in evaluating a manufacturing reshoring decision?” and should guide companies in identifying factors in a reshoring decision. The second one (RQ2) is “How do decision-makers reason with respect to criteria in manufacturing reshoring decisions?” and describes the importance of the identified criteria that come into play during the decision. The third one (RQ3) is “How can the criteria be modeled in decision-support tools for evaluating manufacturing reshoring decisions?” and explores the feasibility of decision support. The research methods involve systematic literature review, multiple case study, modeling, and archival research. The findings show that reshoring is a multi-criteria decision with cost, quality, and delivery time criteria are considered to be more important (high weight) than sustainability criteria (low weight). The reasoning is manifested by inference rules pertaining to the important criteria. Multi-criteria decision-making techniques such as fuzzy inference, AHP, fuzzy-AHP and fuzzy-TOPSIS are feasible for evaluating manufacturing reshoring decisions. While these techniques rely on decision-makers’ ability to specify weights and rules, rule mining is used to extract rules from large datasets. This research contributes through increased knowledge regarding the criteria, reasoning, and modeling of reshoring decisions. Furthermore, the research extrapolates on the theories that are required to move forward when investigating this topic. For practitioners, this research develops tools that can be used in different stages of the decision-making process. For society, the support tools mean making rational decisions on reshoring rather than emotional or politically motivated ones.

Återflyttning av produktion har väckt mycket intresse. Fördelarna med att flytta hem produktion inkluderar ökad kvalitet, flexibilitet, marknadsföring och minskade risker. Dessutom har pandemin avslöjat riskerna med långa leveranskedjor, så det är lämpligt att studera möjligheterna med återflyttning. Det finns behov av mer kunskap om verktyg som kan hjälpa beslutsfattare att ta beslut om att flytta hem produktionen. Syftet med denna studie är att undersöka beslutsstöd för återflyttning av produktionen. Tre forskningsfrågor har formulerats enligt syftet. Den första frågan är “Vilka kriterier bör beslutsfattare överväga vid beslut om återflyttning av produktion?” Svaret för frågan kommer att vägleda beslutsfattaren och företag i med att identifiera kriterier. Den andra frågan är “Hur resonerar beslutsfattare i samband med kriterier vid beslut om återflyttning av produktion?” och den beskriver vikter för de identifierade kriterierna och reglerna som kommer in under beslutet. Den tredje frågan är “Hur kan kriterierna modelleras i ett verktyg för att utvärdera beslut om återflyttning av produktion?” Frågan undersöker olika beslutsmodeller. Studien använder sig av en blandning av metoder, inklusive litteraturstudier, fallstudier, modellering och arkivstudier. De kriterier som beaktas vid beslutet är kostnad, kvalitet och leveranstid, som betraktas som mycket viktiga, medan hållbarhetskriterier inte har samma vikt. Kriterierna är dock dynamiska och kan ändras över tiden. Beslutsreglerna tar hänsyn till de viktiga kriterierna. Fuzzy logic är en möjlig beslutsmodell som kan användas vid beslut om återflyttning. Forskningen bidrar till en ökad förståelse för kriterier, beslutsfattarens resonemang och modellering av återflyttningsbeslut. Dessutom reflekterar forskningen över de teorier som krävs för att gå vidare när man undersöker detta ämne. För praktiker och företag innebär det att utveckla verktyg som kan användas under olika steg i beslutsprocessen. För samhället innebär det att besluten hålls rationella och att undvika emotionella eller politiskt motiverade beslut. Avhandlingen är baserad på sex vetenskapliga artiklar.

Reshoring manufacturing is a strategic decision because of its cost, implications, and complexity. Existing models have largely focused on cost aspects in reshoring decisions and are considered limited in assisting practitioners in the reshoring decision-making process. Variables like cost and quality have been the most important, whereas environment and sustainability seem not a priority, arguing for the myopic nature of these decisions. Therefore, this study employs system dynamics (SD) to expand practitioners’ mental models for the reshoring decision-making process. To do so, first, variables and heuristics are retrieved from the literature. Next, an industry expert is interviewed to have a practitioner’s input. Finally, a descriptive SD model is built by connecting variables and heuristics. The findings indicate that the behavior of the variables in reshoring decisions is dynamic over time. Furthermore, the variables are inter-linked, resulting in non-linear, multi-caused reshoring decisions. The presented SD model allows incorporating the variables that are sometimes difficult to quantify and provides a holistic view of the variables, their relationships, complexities, and the dynamics involved in the reshoring decision-making process. This study contributes to reshoring literature by using SD perspective in the reshoring decision-making process and proposing an SD model for reshoring decision-making. This study assists practitioners in expanding their mental models regarding the reshoring decision-making process. It is further argued that the proposed SD model may work as a generic steppingstone to further develop company-specific feedback-oriented models to support in their reshoring decision-making processes and to support future research on the topic.

The traditional food supply chains are vulnerable to external shocks, and this has been observable during the pandemic. Alternative food networks (AFNs) is seen as a potentially viable alternative to traditional food supply chains. AFNs encompass practices related to local food supply, involve few actors and promote sustainability. The purpose of this research is to identify strategies for sustainable AFNs, that enable growth and resilience during uncertain times. To achieve the purpose, the SCORE (Strengths, Challenges, Opportunities, Responses, Effectiveness) method is investigated. The main findings include an up-to-date overview of the strengths, challenges, opportunities, responses and effectiveness of AFNs in uncertain environments.

Purpose

The existing literature expresses a strong need to develop tools that support the manufacturing reshoring decision-making process. This paper aims to examine the suitability of analytical hierarchy process (AHP)-based tools for initial screening of manufacturing reshoring decisions.

Design/methodology/approach

Two AHP-based tools for the initial screening of manufacturing reshoring decisions are developed. The first tool is based on traditional AHP, while the second is based on fuzzy-AHP. Six high-level and holistic reshoring criteria based on competitive priorities were identified through a literature review. Next, a panel of experts from a Swedish manufacturing company was involved in the overall comparison of the criteria. Based on this comparison, priority weights of the criteria were obtained through a pairwise analysis. Subsequently, the priority weights were used in a weighted-sum manner to evaluate 20 reshoring scenarios. Afterwards, the outputs from the traditional AHP and fuzzy-AHP tools were compared to the opinions of the experts. Finally, a sensitivity analysis was performed to evaluate the stability of the developed decision support tools.

Findings

The research demonstrates that AHP-based support tools are suitable for the initial screening of manufacturing reshoring decisions. With regard to the presented set of criteria and reshoring scenarios, both traditional AHP and fuzzy-AHP are shown to be consistent with the experts' decisions. Moreover, fuzzy-AHP is shown to be marginally more reliable than traditional AHP. According to the sensitivity analysis, the order of importance of the six criteria is stable for high values of weights of cost and quality criteria.

Research limitations/implications

The limitation of the developed AHP-based tools is that they currently only include a limited number of high-level decision criteria. Therefore, future research should focus on adding low-level criteria to the tools using a multi-level architecture. The current research contributes to the body of literature on the manufacturing reshoring decision-making process by addressing decision-making issues in general and by demonstrating the suitability of two decision support tools applied to the manufacturing reshoring field in particular.

Practical implications

This research provides practitioners with two decision support tools for the initial screening of manufacturing reshoring decisions, which will help managers optimize their time and resources on the most promising reshoring alternatives. Given the complex nature of reshoring decisions, the results from the fuzzy-AHP are shown to be slightly closer to those of the experts than traditional AHP for initial screening of manufacturing relocation decisions.

Originality/value

This paper describes two decision support tools that can be applied for the initial screening of manufacturing reshoring decisions while considering six high-level and holistic criteria. Both support tools are applied to evaluate 20 identical manufacturing reshoring scenarios, allowing a comparison of their output. The sensitivity analysis demonstrates the relative importance of the reshoring criteria.

Reshoring of manufacturing to high-cost environments has been gaining attention. Several drivers are usually involved in the reshoring process. This process also requires manufacturing companies to assess their capabilities in relationship to the reshoring drivers. However, the connection between the reshoring drivers and the capabilities that the manufacturing companies have in high-cost environments has received little attention. The purpose of this study is to investigate the connection between the reshoring drivers and critical capabilities, through a transdisciplinary approach. This study was conducted through a literature review. The first step included the investigation of existing literature related to operations capabilities. The second step included the investigation of existing literature related to reshoring drivers. The third step included an investigation of the link between the critical operations capabilities and the reshoring drivers derived from the literature. Both sets of critical operations capabilities and reshoring drivers were linked based on their respective definitions. The findings revealed that there is a connection between operations capabilities and reshoring drivers. This study contributes to the development of both reshoring and operations capabilities research streams, and to practice by identifying the specific operations capabilities that can drive reshoring. 

Purpose: This paper investigates the suitability of fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions.

Design/methodology/approach: Two fuzzy-logic-based support tools are developed together with experts from a Swedish manufacturing firm. The first uses a complete rule base and the second a reduced rule base. Sixteen inference settings are used in both of the support tools.

Findings: The findings show that fuzzy-logic-based support tools are suitable for initial screening of manufacturing reshoring decisions. The developed support tools are capable of suggesting whether a reshoring decision should be further evaluated or not, based on six primary competitiveness criteria. In contrast to existing literature this research shows that it does not matter whether a complete or reduced rule base is used when it comes to accuracy. The developed support tools perform similarly with no statistically significant differences. However, since the interpretability is much higher when a reduced rule base is used and it require fewer resources to develop, the second tool is more preferable for initial screening purposes.

Research limitations/implications: The developed support tools are implemented at a primary-criteria level and to make them more applicable, they should also include the sub-criteria level. The support tools should also be expanded to not only consider competitiveness criteria, but also other criteria related to availability of resources and strategic orientation of the firm. This requires further research with regard to multi-stage architecture and automatic generation of fuzzy rules in the manufacturing reshoring domain.

Practical implications: The support tools help managers to invest their scarce time on the most promising reshoring projects and to make timely and resilient decisions by taking a holistic perspective on competitiveness. Practitioners are advised to choose the type of support tool based on the available data.

Originality/value: There is a general lack of decision support tools in the manufacturing reshoring domain. This paper addresses the gap by developing fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions.

Reshoring decisions are complex due to multiple groups of criteria that have an impact on the decision involved. In order to support this manual decision-making process, more advanced tools need to be developed. The purpose of this paper is to explore a multi-stage fuzzy-logic model to support the reshoring decision-making process through a transdisciplinary approach. Three relevant stages pertaining to reshoring decisions were identified: production resources, production capabilities, and competitive priorities. For each stage, factor loading values were used to create fuzzy rules. The model provides a decision recommendation based on a set of input reshoring scenarios. The research contributes to the reshoring literature providing a multi-stage fuzzy-logic model that simultaneously handles different groups of criteria, and to practitioners by contemplating different key competencies within a company during the reshoring decision process.