Ãîäèøåí àëìàíàõ "Íàó÷íè èçñëåäâàíèÿ íà äîêòîðàíòè"

Îùå ñòàòèè îò òîçè áðîé

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  WORKFORCE EFFICIENCY INCREASE FOR THE ONLINE SALES IN-STORE PICKING OPERATION

  The online food retailing got more attention to itself with the global coronavirus outbreak. Online marketing growth rate reached above 40% in the lockdown months. It became more important to deliver the orders faster than opponents. This study examines one of the biggest food retails company’s in-store picking operation for workforce efficiency ... The online food retailing got more attention to itself with the global coronavirus outbreak. Online marketing growth rate reached above 40% in the lockdown months. It became more important to deliver the orders faster than opponents. This study examines one of the biggest food retails company’s in-store picking operation for workforce efficiency increase. The picker job description and daily work routines observed through observation forms. The results are validated by data extracted from the Collectify system, which is used for picking operation and has all the time stamp of picker’s action. Analyzing data and combining with the output of observation forms, the new picking model proposed for the fresh departments (meat, deli, fruit & vegetable) products. Having two weeks of trial and after realizing the results with the Collectify system data, the new model helped operating costs decrease by 7,7% in the picking operation.

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  ÔÈÍÀÍÑÎÂÎ ÑÒÈÌÓËÈÐÀÍÅ ÇÀ ÈÍÎÂÀÒÈÂÍÈ ÏÎÑÒÈÆÅÍÈß ÍÀ Ó×ÅÍÈÖÈÒÅ

   áúëãàðñêàòà îáðàçîâàòåëíà ñèñòåìà ñúùåñòâóâàò äåìîêðàòè÷íè òðàäèöèè, ñâúðçàíè ñúñ ñúó÷àñòèåòî â óïðàâëåíèåòî íà ïðåäó÷èëèùíîòî è ó÷èëèùíîòî îáðàçîâàíèå. Ñúâðåìåííîòî áúëãàðñêî îáùåñòâî å ïîñòàâåíî ïðåä äèíàìè÷íè ïðîìåíè, îáðàçîâàòåëíàòà íè ñèñòåìà òðÿáâà äà îòãîâîðè íà ïðåäèçâèêàòåëñòâàòà, ñâúðçàíè ñ îáðàçîâàíèåòî íà ìëàäèòå õîðà, çà äà ìîãàò äà ...  áúëãàðñêàòà îáðàçîâàòåëíà ñèñòåìà ñúùåñòâóâàò äåìîêðàòè÷íè òðàäèöèè, ñâúðçàíè ñúñ ñúó÷àñòèåòî â óïðàâëåíèåòî íà ïðåäó÷èëèùíîòî è ó÷èëèùíîòî îáðàçîâàíèå. Ñúâðåìåííîòî áúëãàðñêî îáùåñòâî å ïîñòàâåíî ïðåä äèíàìè÷íè ïðîìåíè, îáðàçîâàòåëíàòà íè ñèñòåìà òðÿáâà äà îòãîâîðè íà ïðåäèçâèêàòåëñòâàòà, ñâúðçàíè ñ îáðàçîâàíèåòî íà ìëàäèòå õîðà, çà äà ìîãàò äà ñå àäàïòèðàò êúì ïàçàðíàòà ñðåäà è êîíêóðåíòîñïîñîáíîñò. ,,Îáðàçîâàíèåòî å â îñíîâàòà íà èíîâàöèèòå, êîèòî äâèæàò èêîíîìèêàòà íà çíàíèåòî, çàòîâà å êëþ÷îâî çà ìëàäåæèòå êàêòî äà ïðèäîáèÿò çíàíèÿ, òàêà è äà ðàçâèÿò â ñåáå ñè îñíîâíèòå óìåíèÿ êàòî êðèòè÷íî ìèñëåíå, êðåàòèâíîñò è óìåíèÿ çà âçåìàíå íà ðåøåíèÿ.” (Èíñòèòóò çà ìåæäóíàðîäíî ñúòðóäíè÷åñòâî, 5, 2016). Îñíîâíîòî âíèìàíèå ùå áúäå íàñî÷åíî êúì óïðàâëåíèåòî íà ñðåäñòâàòà ,,Ôîíä ôèíàíñîâî ñòèìóëèðàíå íà ó÷åíèöè”, êîåòî å ïðåäìåò íà íàñòîÿùàòà ðàçðàáîòêàòà. Îáåêò íà èçñëåäâàíåòî ñà íà÷èíúò è ñðåäñòâàòà çà ôèíàíñîâîòî ñòèìóëèðàíå íà ó÷åíèöèòå ñ èíîâàòèâíè ïîñòèæåíèÿ, ñúáðàíè îò ðàáîòîäàòåëèòå (áèçíåñà) íà ìåñòíî íèâî è ðàçïðåäåëÿíåòî íà ñðåäñòâàòà ïî åôåêòèâåí è ñïðàâåäëèâ íà÷èí. Öåëòà íà ñòàòèÿòà å äà èçòúêíå ñúùíîñòòà íà îáùåñòâåíèòå ñúâåòè êàòî êîëåêòèâåí îðãàí çà ãðàæäàíñêè êîíòðîë â óïðàâëåíèå íà ó÷èëèùåòî, ðàçïðåäåëÿíåòî íà ôèíàíñîâ ðåñóðñ çà ñòèìóëèðàíå íà èçÿâåíè ó÷åíèöè â èíîâàòèâíè ïîñòèæåíèÿ. Ïîëçâàíè ñà êëàñè÷åñêèòå àíàëèòè÷íè ìåòîäè – èíäóêöèÿ, äåäóêöèÿ, êðèòè÷åí àíàëèç è ñèíòåç.

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  ÅÂÐÎÏÅÉÑÊÀÒÀ ÒÚÐÃÎÂÑÊÀ ÏÎËÈÒÈÊÀ Â ÏÎÄÊÐÅÏÀ ÍÀ ÐÀÇÂÈÂÀÙÈÒÅ ÑÅ ÈÊÎÍÎÌÈÊÈ

   íàñòîÿùàòà ðàçðàáîòêà ñà ïðåäñòàâåíè îñíîâíèòå ïðîáëåìè, êîèòî íàëàãàò ïðèëàãàíåòî íà ïîëèòèêè è ìåðêè çà ñòèìóëèðàíå íà áëàãîñúñòîÿíèåòî è ðàçâèòèåòî íà ðàçâèâàùèòå ñå èêîíîìèêè. Îñíîâíàòà öåë íà èçñëåäâàíåòî å äà ñå îòêðîÿò ïðè÷èíèòå, ïîðàäè êîèòî ñå íàëàãà ïîäïîìàãàíå ðàçâèòèåòî íà ïîñî÷åíèòå èêîíîìèêè è äà ñå ïðîñëåäÿò ìåðêèòå â ðàìêèòå íà ...  íàñòîÿùàòà ðàçðàáîòêà ñà ïðåäñòàâåíè îñíîâíèòå ïðîáëåìè, êîèòî íàëàãàò ïðèëàãàíåòî íà ïîëèòèêè è ìåðêè çà ñòèìóëèðàíå íà áëàãîñúñòîÿíèåòî è ðàçâèòèåòî íà ðàçâèâàùèòå ñå èêîíîìèêè. Îñíîâíàòà öåë íà èçñëåäâàíåòî å äà ñå îòêðîÿò ïðè÷èíèòå, ïîðàäè êîèòî ñå íàëàãà ïîäïîìàãàíå ðàçâèòèåòî íà ïîñî÷åíèòå èêîíîìèêè è äà ñå ïðîñëåäÿò ìåðêèòå â ðàìêèòå íà åâðîïåéñêà òúðãîâñêà ïîëèòèêà.  ðàçðàáîòêàòà ñà ðàçãëåäàíè îñíîâíèòå ïðîáëåìè ïðåä òúðãîâèÿòà ìåæäó ðàçâèòèòå è ðàçâèâàùèòå ñå èêîíîìèêè è ñà îòêðîåíè íÿêîè îò ïðè÷èíèòå çà ïðåïÿòñòâèÿòà ïðåä òúðãóâàíåòî. Ðàçãúðíà-òè ñà è âàðèàíòè çà ðàçðåøàâàíåòî íà ïðîáëåìàòèêàòà.